{ "count" : 55679, "data" : [ { "id" : "6a2c6ace74d8ee00a090e15e", "title" : "Data Annotation Specialist", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 9.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-16T00:34:29.192", "fingerprint" : "f0037504820c4319c0dcd5849cdd4b980f6d0d88384743da6b213fee3b834e01", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4232528009", "externalId" : "4232528009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "High School", "majorSkills" : "Data Annotation, AI Development, LLM", "majorSkillsList" : [ "Data Annotation", "AI Development", "LLM" ], "coreResponsibilities" : "Rate/assess AI model performance, Label content elements, Assign predefined categories or labels, Evaluate content quality and/or appropriateness, Generate labels to advance understanding, Create additional training data, Apply transformations to data, Review data and identify product feature functionality, Label model outputs, Order or rank items, Create prompts or questions for AI, Evaluate content relevance, Generate responses to prompts, Rewrite existing text, Produce concise summaries, Convert spoken language to text, Convert language from one to another, Gather and compile data", "domainKnowledge" : "Generative AI; Large Language Models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large Language Models" ], "qualificationsBasic" : "High School Diploma or higher, Professional or Expert level proficiency (C1/C2) in English", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Data Annotators to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A High School Diploma or higher is required. Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $9 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.", "summaryDescription" : "Data Annotation Specialist at Innodata Inc.. Skills: Data Annotation, AI Development, LLM. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T19:09:07.533", "createdAt" : "2026-06-14T19:09:07.533", "lastUpdated" : "2026-06-16T00:34:29.192", "ingestTimestamp" : "2026-06-14T19:09:07.533", "mongoId" : "6a2c6ace74d8ee00a090e15e", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 18720, "salaryBand" : "<30k", "hasSalary" : true, "allSkills" : [ "Data Annotation", "AI Development", "LLM", "Generative AI", "Large Language Models" ], "skillCount" : 5, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2ca05474d8ee00a09a1e59", "title" : "Data Annotation Specialist", "company" : "Saronic Technologies", "industry" : "Software", "salary" : { "min" : 42000.0, "max" : 58000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an Entry-level Data Annotation Specialist in Austin, United States, adjusted for the technology industry and contract employment type." }, "location" : "Austin, TX", "locations" : [ "Austin, TX" ], "timestamp" : "2026-06-16T02:28:21.795", "fingerprint" : "86d6befb0b593bae139fe66e3e03918ebb395121850177663e1c5ae2e77a5e83", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/saronic/f418b71d-d2e1-49e3-9a54-b41a2c5f5e97/application", "externalId" : "f418b71d-d2e1-49e3-9a54-b41a2c5f5e97", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Austin", "state" : "Texas", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "30.2711286,-97.7436995" } ], "locationText" : "Austin, Texas, United States", "employmentType" : "CONTRACT", "technicalSkills" : "Computer vision", "hardSkillsList" : [ "Data annotation", "Image annotation", "Video annotation", "Sensor data annotation", "Object identification", "Quality review", "Labeling guidelines" ], "hardSkills" : [ { "name" : "Data annotation", "level" : "intermediate" }, { "name" : "Image annotation", "level" : "intermediate" }, { "name" : "Video annotation", "level" : "intermediate" }, { "name" : "Sensor data annotation", "level" : "intermediate" }, { "name" : "Object identification", "level" : "intermediate" }, { "name" : "Quality review", "level" : "intermediate" }, { "name" : "Labeling guidelines", "level" : "intermediate" } ], "majorSkills" : "Data annotation, Computer vision", "majorSkillsList" : [ "Data annotation", "Computer vision" ], "coreResponsibilities" : "Annotate visual datasets, Review visual datasets, Train machine-learning models, Evaluate machine-learning models, Annotate image data, Annotate video data, Annotate infrared data, Annotate sensor data, Identify vessels, Identify objects, Identify environmental features, Maintain accuracy, Maintain consistency, Maintain productivity, Apply labeling guidelines, Escalate unclear edge cases, Perform manual annotation, Review auto-labeled data, Support priority project deadlines", "teamCollaboration" : "Support technical team", "domainKnowledge" : "Maritime autonomy; Maritime perception", "domainList" : [ "maritime-autonomy", "maritime-perception" ], "domainSpecificKnowledge" : [ "Maritime autonomy", "Maritime perception" ], "toolProficiency" : [ "Labelbox", "CVAT" ], "qualificationsBasic" : "Prior experience in computer vision data annotation, Familiarity with annotation tools, Experience with annotation types, Visual pattern recognition, Spatial reasoning, Attention to detail, Comfortable performing repetitive work, Able to adapt to changing priorities, Communication skills, Willingness to ask questions, Willingness to accept feedback, Willingness to collaborate with the team", "qualificationsPreferred" : "Basic understanding of maritime environments, Basic understanding of autonomous systems, Basic understanding of robotics, Basic understanding of defense technology", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Saronic Technologies is a leader in revolutionizing autonomy at sea, dedicated to developing state-of-the-art solutions that enhance maritime operations through autonomous and intelligent platforms. JOB OVERVIEW We are seeking a Data Annotation Specialist to annotate and review visual datasets used to train and evaluate machine-learning models for maritime perception and autonomy. This role supports our software, perception, and autonomy teams by ensuring labeled data is accurate, consistent, and useful for model development. The ideal candidate has prior computer vision annotation experience, strong visual attention to detail, and the ability to maintain speed and accuracy through repetitive labeling work. This person should be comfortable following detailed instructions, adapting as labeling rules change, and supporting a fast-moving technical team. This is an on-site, full-time contract role with an intended path to full-time conversion based on performance and business needs. Upon conversion, the employee would be eligible for Saronic’s standard full-time benefits. This position reports to the Data Annotation Manager. RESPONSIBILITIES - Annotate and review large volumes of image, video, infrared, and other sensor data using computer vision labeling methods. - Identify vessels, objects, environmental features, and other elements relevant to maritime autonomy. - Maintain accuracy, consistency, and productivity across repetitive, detail-heavy datasets. - Apply evolving labeling guidelines and escalate unclear edge cases when needed. - Perform both manual annotation work and quality review of auto-labeled data as needed. - Willingness to support priority project deadlines when needed. QUALIFICATIONS - Prior experience in computer vision data annotation or labeling. - Familiarity with annotation tools such as Labelbox, CVAT, or similar - Experience with annotation types such as segmentation masks, bounding boxes, key points, object tracking, or classification. - Strong visual pattern recognition, spatial reasoning, and attention to detail. - Comfortable performing repetitive, process-driven work for extended periods while maintaining quality. - Able to adapt to changing project priorities, labeling rules, and quality standards in a fast-paced environment. - Strong communication skills and willingness to ask questions, accept feedback, and collaborate with the team. - Basic understanding of maritime environments, autonomous systems, robotics, or defense technology is a plus. Saronic CCPA Notice for Candidates and California Employees https://saronic-assets-public.s3.us-east-2.amazonaws.com/Saronic%20CCPA%20Notice%20for%20Candidates%20and%20California%20Employees.pdf If this role is based in the United States, it requires access to export-controlled information or items that require “U.S. Person” status. As defined by U.S. law, individuals who are any one of the following are considered to be a “U.S. Person”: (1) U.S. citizens, (2) legal permanent residents (a.k.a. green card holders), and (3) certain protected classes of asylees and refugees, as defined in 8 U.S.C. 1324b(a)(3) https://www.govinfo.gov/link/uscode/8/1324b. Saronic does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits. We are also committed to providing reasonable accommodations for qualified individuals with disabilities.", "summaryDescription" : "Data Annotation Specialist at Saronic Technologies. Skills: Data annotation, Computer vision. Annotate visual datasets. Review visual datasets", "createdAt" : "2026-06-14T18:14:23.473", "lastUpdated" : "2026-06-16T02:28:21.795", "ingestTimestamp" : "2026-06-14T18:14:23.473", "mongoId" : "6a2ca05474d8ee00a09a1e59", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 42000, "salaryAnnualMax" : 58000, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data annotation", "Image annotation", "Video annotation", "Sensor data annotation", "Object identification", "Quality review", "Labeling guidelines", "Computer vision", "Maritime autonomy", "Maritime perception", "Labelbox", "CVAT" ], "skillCount" : 12, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.7777778, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6ace74d8ee00a090e15c", "title" : "Data Annotation Specialist", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 31000.0, "max" : 45000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an entry-level Data Annotation Specialist in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T05:05:47.945", "fingerprint" : "6ae7284a99bb129de52256554a1397590a9b634cdf46c243c80a2b3bfef16778", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4232498009", "externalId" : "4232498009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "High School", "technicalSkills" : "AI, Generative AI, Large Language Models, Machine Learning", "hardSkillsList" : [ "Data annotation", "Content evaluation", "Data transformation", "Text summarization", "Speech to text", "Translation", "Data gathering", "Prompt creation", "Content relevance evaluation" ], "hardSkills" : [ { "name" : "Data annotation", "level" : "intermediate" }, { "name" : "Content evaluation", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Speech to text", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" }, { "name" : "Prompt creation", "level" : "intermediate" }, { "name" : "Content relevance evaluation", "level" : "intermediate" } ], "majorSkills" : "Data annotation, AI development, LLM training", "majorSkillsList" : [ "Data annotation", "AI development", "LLM training" ], "coreResponsibilities" : "Rate/assess AI model performance, Label content elements, Assign predefined categories/labels, Evaluate content quality/appropriateness, Generate labels for concepts/trends, Create training data via transformations, Review data for product feature function, Label model outputs, Order/rank items by criteria, Create prompts for AI systems, Evaluate content relevance, Generate responses from AI systems, Rewrite text preserving meaning, Produce concise summaries, Convert audio to text, Convert language between languages, Gather and compile data", "domainKnowledge" : "Generative AI; Large Language Models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large Language Models" ], "qualificationsBasic" : "High School Diploma or higher, Professional or Expert level proficiency (C1/C2) in English", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Data Annotation Specialists to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A High School Diploma or higher is required. Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $9 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.", "summaryDescription" : "Data Annotation Specialist at Innodata Inc.. Skills: Data annotation, AI development, LLM training. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T07:55:31.054", "createdAt" : "2026-06-14T07:55:31.054", "lastUpdated" : "2026-06-15T05:05:47.945", "ingestTimestamp" : "2026-06-14T07:55:31.054", "mongoId" : "6a2c6ace74d8ee00a090e15c", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 31000, "salaryAnnualMax" : 45000, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data annotation", "Content evaluation", "Data transformation", "Text summarization", "Speech to text", "Translation", "Data gathering", "Prompt creation", "Content relevance evaluation", "AI development", "LLM training", "Generative AI", "Large Language Models" ], "skillCount" : 13, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "69fa628c4c40e2acd166e050", "title" : "Data Annotation Specialist, Arabic Language Najdi/Hijazi Dialect", "company" : "Cohere", "industry" : "Data Quality (Contract)", "salary" : { "min" : 30.0, "max" : 30.0, "currency" : "CAD", "frequency" : "yearly" }, "location" : "Canada", "locations" : [ "Canada", "Toronto", "Calgary", "Montreal", "Vancouver" ], "timestamp" : "2026-05-06T01:04:01.678", "fingerprint" : "d14b60de5dd9f4f26dfbfb4986c6b3fbbf6921cd5fc00abd80ac7480f4c62c64", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/cohere/23c35d20-e31e-42bb-a4dc-88a8e063061a/application", "externalId" : "23c35d20-e31e-42bb-a4dc-88a8e063061a", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Canada", "continent" : "na" } ], "locationText" : "Canada", "employmentType" : "CONTRACT", "technicalSkills" : "JSON, TSV, CSV, Markdown", "professionalSkills" : [ "Data Manipulation" ], "hardSkillsList" : [ "Arabic (Najdi/Hijazi) Writing", "Arabic (Najdi/Hijazi) Translation", "Data Manipulation", "Labeling", "Ranking", "Auditing", "Correcting text output", "Reading and text-based tasks", "Preference-based tasks", "JSON/TSV/CSV/Markdown data manipulation" ], "softSkillsList" : [ "Attention to detail", "Commitment to accuracy", "High tolerance for repetitive and monotonous work", "Ability to follow complex instructions", "Navigate ambiguity", "Work independently", "Superb sense of urgency", "Time management", "Curiosity about technology", "Creative problem solving" ], "hardSkills" : [ { "name" : "Arabic (Najdi/Hijazi) Writing", "level" : "intermediate" }, { "name" : "Arabic (Najdi/Hijazi) Translation", "level" : "intermediate" }, { "name" : "Data Manipulation", "level" : "intermediate" }, { "name" : "Labeling", "level" : "intermediate" }, { "name" : "Ranking", "level" : "intermediate" }, { "name" : "Auditing", "level" : "intermediate" }, { "name" : "Correcting text output", "level" : "intermediate" }, { "name" : "Reading and text-based tasks", "level" : "intermediate" }, { "name" : "Preference-based tasks", "level" : "intermediate" }, { "name" : "JSON/TSV/CSV/Markdown data manipulation", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Attention to detail" }, { "name" : "Commitment to accuracy" }, { "name" : "High tolerance for repetitive and monotonous work" }, { "name" : "Ability to follow complex instructions" }, { "name" : "Navigate ambiguity" }, { "name" : "Work independently" }, { "name" : "Superb sense of urgency" }, { "name" : "Time management" }, { "name" : "Curiosity about technology" }, { "name" : "Creative problem solving" } ], "majorSkills" : "Arabic (Najdi/Hijazi) Language Proficiency, Data Annotation, Data Quality Assurance", "majorSkillsList" : [ "Arabic (Najdi/Hijazi) Language Proficiency", "Data Annotation", "Data Quality Assurance" ], "coreResponsibilities" : "Label and Rank machine learning data with advanced proficiency in Arabic (Najdi/Hijazi), ensuring data integrity and quality., Audit and Correct any inaccuracies in language data (may include text, image, JSON, TSV/CSV, Markdown), maintaining the highest standard of data accuracy., Efficiently complete reading and text-based assignments, with high attention to detail., Evaluate and complete preference-based tasks, assessing which responses in Arabic (Najdi/Hijazi) best conform to project guidelines., Identify and suggest opportunities for improving data quality and model performance in Arabic (Najdi/Hijazi) language tasks., Provide feedback to cross-functional team members, particularly on Arabic (Najdi/Hijazi) language-related matters., Maintain meticulous attention to detail while performing repetitive and precise tasks, particularly when working with language data.", "teamCollaboration" : "Collaborate and communicate effectively, providing feedback to cross-functional team members, particularly on Arabic (Najdi/Hijazi) language-related matters.", "domainKnowledge" : "Arabic (Najdi/Hijazi) Language", "domainList" : [ "arabic-najdi-hijazi-language" ], "domainSpecificKnowledge" : [ "Arabic (Najdi/Hijazi) Language" ], "toolProficiency" : [ "JSON", "TSV", "CSV", "Markdown" ], "communicationSkills" : "Communicate effectively", "innovationCreativity" : "Tackling problems in creative ways", "problemSolvingSkills" : "Navigate ambiguity; Tackling problems in creative ways", "specialRequirements" : "Part-time independent contractor position, Commit to 16 hours per week minimum, BYOD (Bring Your Own Device - laptop), 12 month contract, Work involves exposure to not safe for work (NSFW) text content as part of data annotation tasks, including explicit, offensive, or other inappropriate material.", "qualificationsBasic" : "Native or near-native proficiency in Arabic (Najdi/Hijazi), Excellent command over English, Expert reading and writing skills, Basic familiarity with JSON/TSV/CSV/Markdown data manipulation, Attention to detail and commitment to accuracy, High tolerance for repetitive and monotonous work, Ability to follow complex instructions, navigate ambiguity and work independently, Superb sense of urgency and time management, Curiosity about technology and a knack for tackling problems in creative ways, A reliable laptop", "qualificationsPreferred" : "Performance incentives included", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Who are we? Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers. Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products. Join us on our mission and shape the future! Why this role? We are on a mission to build machines that understand the world and make them safely accessible to all. Data quality is foundational to this process. Machines (or Large Language Models to be exact) learn in similar ways to humans - by way of feedback. By labelling, ranking, auditing, and correcting text output, you will improve Large Language Model’s performance for iterations to come, thus having a lasting impact on Cohere’s tech. Cohere seeks dynamic and dedicated Data Annotators with exceptional Arabic (Najdi/Hijazi) Writing, Translation, and Data Manipulation skill. Please Note: This is a part-time independent contractor position available within Canada. We seek candidates who are able to commit to 16 hours per week minimum at a 30 CAD/hour contract rate. This role is BYOD \uD83D\uDCBB - Bring Your Own Device (laptop). Remote work within Canada. 12 month contract. Performance incentives included! As a Data Annotation Specialist, you will: - Label and Rank: Accurately label and rank machine learning data with advanced proficiency in Arabic (Najdi/Hijazi), ensuring data integrity and quality. - Audit and Correct: Scrutinize and rectify any inaccuracies in language data (may include text, image, JSON, TSV/CSV, Markdown), maintaining the highest standard of data accuracy. - Reading and Text-Based Tasks: Efficiently complete reading and text-based assignments, with high attention to detail. - Preference-Based Tasks: Evaluate and complete tasks, assessing which responses in Arabic (Najdi/Hijazi) best conform to project guidelines. - Recommend Optimizations: Identify and suggest opportunities for improving data quality and model performance in Arabic (Najdi/Hijazi) language tasks. - Provide Feedback: Collaborate and communicate effectively, providing feedback to cross-functional team members, particularly on Arabic (Najdi/Hijazi) language-related matters. - Detail-Oriented Execution: Maintain meticulous attention to detail while performing repetitive and precise tasks, particularly when working with language data. You may be a good fit if you have: - Language Proficiency: Native or near-native proficiency in Arabic (Najdi/Hijazi); excellent command over English. - Expert reading and writing skills - which you are ready to prove on our written test. - Basic familiarity with JSON/TSV/CSV/Markdown data manipulation. - Strong attention to detail and commitment to accuracy - you’re the type to proofread all of your emails! - High tolerance for repetitive and monotonous work. - Ability to follow complex instructions, navigate ambiguity and work independently. - Superb sense of urgency and time management. - Curiosity about technology and a knack for tackling problems in creative ways. - A reliable laptop. The Candidate Journey: Initial Screening - Once you have submitted your application our Talent Team will review your resume and writing samples. Virtual Annotation Test - This assignment will test your written skill through various language-based tasks, such as a a writing sample, interacting with a chat bot, and more. Video Screen - If selected to move forward, you will have a short video call with a member of our Operations Team! Offer - Independent Contractor Agreement As an independent contractor, you maintain control over how you complete your work and may work with multiple clients simultaneously, although we ask you to declare if any of these are with a direct competitor of Cohere and maintain IP confidentiality of the Cohere project. Independent contractors are not eligible for health benefits or other benefits provided to employees. Compensation for services is provided to contractors by contractors invoicing for services provided pursuant to the terms of our agreement with the contractor. It is important to understand that as an independent contractor, continuous work is not guaranteed. The client-contractor relationship is fundamentally project-based, meaning engagements may be temporary, periodic, or intermittent based on our organizational needs and project availability. As an independent contractor, you should anticipate fluctuations in workflow and therefore compensation for services when Cohere does not require as many hours of services in a week. Prospective candidates, please be advised: this role involves working with human generated and model generated tasks that may involve exposure to not safe for work (NSFW) text content as part of data annotation tasks, including explicit, offensive, or other inappropriate material. If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. Full-Time Employees at Cohere enjoy these Perks: \uD83E\uDD1D An open and inclusive culture and work environment \uD83E\uDDD1‍\uD83D\uDCBB Work closely with a team on the cutting edge of AI research \uD83C\uDF7D Weekly lunch stipend, in-office lunches & snacks \uD83E\uDDB7 Full health and dental benefits, including a separate budget to take care of your mental health \uD83D\uDC23 100% Parental Leave top-up for up to 6 months \uD83C\uDFA8 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement \uD83C\uDFD9 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend ✈️ 6 weeks of vacation (30 working days!)", "summaryDescription" : "Data Annotation Specialist, Arabic Language Najdi/Hijazi Dialect at Cohere. Skills: Arabic (Najdi/Hijazi) Language Proficiency, Data Annotation, Data Quality Assurance. Label and Rank machine learning data with advanced proficiency in Arabic (Najdi/Hijazi), ensuring data integrity and quality.. Audit and Correct any inaccuracies in language data (may include text, image, JSON, TSV/CSV, Markdown), maintaining the highest standard of data accuracy.", "postedDate" : "2026-05-06T01:02:35.522", "createdAt" : "2026-05-06T01:02:35.522", "lastUpdated" : "2026-05-06T01:04:01.678", "ingestTimestamp" : "2026-05-06T01:02:35.522", "mongoId" : "69fa628c4c40e2acd166e050", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 62400, "salaryAnnualMax" : 62400, "salaryBand" : "50k-75k", "hasSalary" : true, "allSkills" : [ "Arabic (Najdi/Hijazi) Writing", "Arabic (Najdi/Hijazi) Translation", "Data Manipulation", "Labeling", "Ranking", "Auditing", "Correcting text output", "Reading and text-based tasks", "Preference-based tasks", "JSON/TSV/CSV/Markdown data manipulation", "Attention to detail", "Commitment to accuracy", "High tolerance for repetitive and monotonous work", "Ability to follow complex instructions", "Navigate ambiguity", "Work independently", "Superb sense of urgency", "Time management", "Curiosity about technology", "Creative problem solving", "Arabic (Najdi/Hijazi) Language Proficiency", "Data Annotation", "Data Quality Assurance", "Arabic (Najdi/Hijazi) Language", "JSON", "TSV", "CSV", "Markdown" ], "skillCount" : 28, "jobCategory" : "data-science", "jobSubcategory" : "multilingual-annotation---arabic", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Tech / AI / Software", "llmIndustryConfidence" : 1.0 }, { "id" : "6a2c6ace74d8ee00a090e135", "title" : "AI Annotation Specialist", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 35000.0, "max" : 50000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level AI Annotation Specialists in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T21:25:40.257", "fingerprint" : "11337ac1370825ef83977315c3b15a22a59adfd7c158f493a190fdf7478820b6", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4232730009", "externalId" : "4232730009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "High School", "majorSkills" : "Data Annotation, AI Development, LLM", "majorSkillsList" : [ "Data Annotation", "AI Development", "LLM" ], "coreResponsibilities" : "Rate/assess AI model performance, Label content elements, Assign predefined categories or labels, Evaluate content quality/appropriateness, Generate labels for concept understanding, Create training data by applying transformations, Review data to identify feature functionality, Label model outputs, Order or rank items based on criteria, Create prompts for AI systems, Evaluate content relevance, Generate responses to prompts, Rewrite existing text, Produce concise summaries, Convert spoken language to text, Convert text from one language to another, Gather and compile data for AI models", "domainKnowledge" : "Generative AI; Large Language Models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large Language Models" ], "qualificationsBasic" : "High School Diploma or higher, Professional or Expert level proficiency (C1/C2) in English", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Data Annotators to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A High School Diploma or higher is required. Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $9 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.", "summaryDescription" : "AI Annotation Specialist at Innodata Inc.. Skills: Data Annotation, AI Development, LLM. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T19:15:23.902", "createdAt" : "2026-06-14T19:15:23.902", "lastUpdated" : "2026-06-15T21:25:40.257", "ingestTimestamp" : "2026-06-14T19:15:23.902", "mongoId" : "6a2c6ace74d8ee00a090e135", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 35000, "salaryAnnualMax" : 50000, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data Annotation", "AI Development", "LLM", "Generative AI", "Large Language Models" ], "skillCount" : 5, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6ace74d8ee00a090e133", "title" : "AI Annotation Specialist", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 35000.0, "max" : 50000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level AI Annotation Specialist in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T06:46:01.277", "fingerprint" : "20e504cbb3175f7c029119e0ec046554440f591ae739a4645f2e1750b04d0786", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4234805009", "externalId" : "4234805009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "High School", "technicalSkills" : "AI, Machine learning, Generative AI, Large language models, LLMs", "professionalSkills" : [ "Data engineering", "Evaluation frameworks", "Human expertise" ], "hardSkillsList" : [ "Data annotation", "Content labeling", "Data transformation", "Data review", "Data generation", "Prompt creation", "Response generation", "Text summarization", "Speech to text", "Translation", "Data gathering", "Data compilation" ], "hardSkills" : [ { "name" : "Data annotation", "level" : "intermediate" }, { "name" : "Content labeling", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Data review", "level" : "intermediate" }, { "name" : "Data generation", "level" : "intermediate" }, { "name" : "Prompt creation", "level" : "intermediate" }, { "name" : "Response generation", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Speech to text", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" }, { "name" : "Data compilation", "level" : "intermediate" } ], "majorSkills" : "AI Annotation, LLM Development", "majorSkillsList" : [ "AI Annotation", "LLM Development" ], "coreResponsibilities" : "Rate/assess AI model performance, Label content elements, Assign predefined categories/labels, Evaluate content quality/appropriateness, Generate labels for concepts, Create training data for ML models, Apply transformations to data, Review data for product feature function, Label model outputs, Identify branded content, Order or rank items, Create prompts for AI systems, Evaluate content relevancy, Generate responses to prompts, Rewrite existing text, Produce concise summaries, Convert spoken language to text, Convert content between languages, Gather and compile data for AI models", "domainKnowledge" : "Generative AI; Large language models; LLMs", "domainList" : [ "generative-ai", "large-language-models", "llms" ], "domainSpecificKnowledge" : [ "Generative AI", "Large language models", "LLMs" ], "outcomesObjectives" : "Build AI systems that can be trusted at scale; Advance the responsible advancement of artificial intelligence", "qualificationsBasic" : "High School Diploma or higher, Professional or Expert level proficiency (C1/C2) in English", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious AI Annotation Specialists to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A High School Diploma or higher is required. Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $9 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.", "summaryDescription" : "AI Annotation Specialist at Innodata Inc.. Skills: AI Annotation, LLM Development. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T09:31:18.177", "createdAt" : "2026-06-14T09:31:18.177", "lastUpdated" : "2026-06-15T06:46:01.277", "ingestTimestamp" : "2026-06-14T09:31:18.177", "mongoId" : "6a2c6ace74d8ee00a090e133", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 35000, "salaryAnnualMax" : 50000, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data annotation", "Content labeling", "Data transformation", "Data review", "Data generation", "Prompt creation", "Response generation", "Text summarization", "Speech to text", "Translation", "Data gathering", "Data compilation", "AI Annotation", "LLM Development", "Data engineering", "Evaluation frameworks", "Human expertise", "Generative AI", "Large language models", "LLMs" ], "skillCount" : 20, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6ace74d8ee00a090e137", "title" : "AI Annotation Specialist", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 31000.0, "max" : 45000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level AI Annotation Specialists in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T03:47:37.663", "fingerprint" : "a0d497d099f6a5738f4d29e68e441254cacf9292b7d872f7c312544a959b9d3d", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4232733009", "externalId" : "4232733009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "High School", "technicalSkills" : "AI, LLMs, Machine learning", "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Data compilation" ], "hardSkills" : [ { "name" : "Data labeling", "level" : "intermediate" }, { "name" : "Content evaluation", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" }, { "name" : "Data compilation", "level" : "intermediate" } ], "majorSkills" : "Data annotation, AI development, LLM training", "majorSkillsList" : [ "Data annotation", "AI development", "LLM training" ], "coreResponsibilities" : "Rate AI model performance, Assess AI model behavior, Label content elements, Assign predefined categories, Evaluate content quality, Evaluate content appropriateness, Generate labels, Create training data, Apply data transformations, Modify images, Generate new text, Alter audio/video signals, Review data, Identify product feature function, Label model outputs, Identify content type, Order items, Rank items, Create prompts, Create questions, Evaluate content relevance, Generate responses, Rewrite existing text, Preserve original meaning, Produce concise summaries, Convert spoken language, Convert audio content, Convert text, Convert spoken language to text, Convert text to another language, Convert spoken language to another language, Gather data, Compile data", "teamCollaboration" : "Global contributor community; Subject Matter Expert on Demand program", "domainKnowledge" : "Generative AI; Large language models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large language models" ], "qualificationsBasic" : "High School Diploma or higher, Professional or Expert level proficiency in English", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certs", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Data Annotators to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A High School Diploma or higher is required. Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $9 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.", "summaryDescription" : "AI Annotation Specialist at Innodata Inc.. Skills: Data annotation, AI development, LLM training. Rate AI model performance. Assess AI model behavior", "postedDate" : "2026-06-13T21:29:06.790", "createdAt" : "2026-06-13T21:29:06.790", "lastUpdated" : "2026-06-15T03:47:37.663", "ingestTimestamp" : "2026-06-13T21:29:06.790", "mongoId" : "6a2c6ace74d8ee00a090e137", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 31000, "salaryAnnualMax" : 45000, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Data compilation", "Data annotation", "AI development", "LLM training", "Generative AI", "Large language models" ], "skillCount" : 10, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "69c94a759bc74574cbbb3da1", "title" : "AI Data Annotation Specialist (French)", "company" : "Amazon MLS Poland Sp. z o.o. - K69", "industry" : "Administrative Support, Machine Learning Data Operatio, Artificial Intelligence", "salary" : { "min" : 75000.0, "max" : 110000.0, "currency" : "PLN", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an AI Data Annotation Specialist in Gdansk, Poland, adjusted for mid-seniority and the technology industry." }, "location" : "Gdansk, Pomeranian Voivodeship, POL", "locations" : [ "Gdansk, Pomeranian Voivodeship, POL" ], "timestamp" : "2026-06-14T23:54:59.758", "fingerprint" : "02815d1d8cff5fff3e421ad50d6097cdba7686e6a403074f70b698cd6e0deeb7", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3191110/apply", "externalId" : "85ff774f-1a80-4c65-96a8-5aef6c520643", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Gdansk", "state" : "Pomeranian Voivodeship", "country" : "Poland", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "54.4288032,18.7983270" } ], "locationText" : "Gdansk, Pomeranian Voivodeship, Poland", "employmentType" : "FULL_TIME", "professionalSkills" : [ "Data labelling", "Dialogue evaluation" ], "hardSkillsList" : [ "Root cause analysis", "Error pattern identification" ], "softSkillsList" : [ "Eye for detail", "Individuality", "Creative mind" ], "hardSkills" : [ { "name" : "Root cause analysis", "level" : "intermediate" }, { "name" : "Error pattern identification", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Eye for detail" }, { "name" : "Individuality" }, { "name" : "Creative mind" } ], "majorSkills" : "Data annotation, LLM development", "majorSkillsList" : [ "Data annotation", "LLM development" ], "coreResponsibilities" : "Maintain strict confidentiality, Work with different data types, Deliver high-quality labelled data, Meet KPIs, Generate high quality human insight data, Make sound judgments, Make logical decisions, Demonstrate support on daily operational deliverables, Analyze root causes, Identify error patterns, Propose solutions, Enhance quality of labeling tasks, Identify process issues, Identify operational issues, Suggest changes to unblock operations, Provide floor support, Clarify internal queries", "teamCollaboration" : "Diverse team; Daily operational deliverables", "domainKnowledge" : "Generative AI; Large language models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large language models" ], "toolProficiency" : [ "In-house tools" ], "communicationSkills" : "Business writing skills; Professional correspondence", "documentationSkills" : "Create reports; Create proposals", "continuousLearning" : "Trainings", "innovationCreativity" : "Invent; Simplify; Build", "problemSolvingSkills" : "Structured problem-solving; Root cause analysis; Error pattern identification", "outcomesObjectives" : "Meet our KPIs", "qualificationsBasic" : "Associate's Degree or related work experience, C1+ or equivalent fluency in French, B2+ in spoken and written English, Business writing skills, Advanced reading comprehension, Developed analytical thinking, Structured problem-solving capabilities, Interpret and implement detailed instructions, Proficient research skills, Gathering and synthesizing information, Proven attention to detail", "qualificationsPreferred" : "Bachelor's degree in a relevant field, 2+ years of professional work experience, Demonstrated task execution ability, Leverage open-source resources effectively, Adapt to fast-paced environments, 2-3 years project coordination experience, 2-3 years project management experience, Experience managing stakeholder relationships, Advanced proficiency in Microsoft Office Suite, Advanced proficiency in common business applications", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "AI is the most transformational technology of our time, capable of tackling some of humanity’s most challenging problems. Amazon is investing in generative AI and the responsible development and deployment of large language models (LLMs) across all of our businesses. Come build the future of human-technology interaction with us. We are looking for those candidates who just don’t think out of the box, but make the box they are in ‘Bigger’. The future is now, do you want to be a part of it? Then read on! Key job responsibilities - Maintain and follow strict confidentiality as customer privacy is our most important tenet - Work with a range of different types of data including, but not limited to: text, speech, audio, image, and video - Deliver high-quality labelled data, using guidelines provided to meet our KPIs and using in-house tools and software, as part of Amazon's commitment to developing and deploying AI responsibly. - Demonstrate proficiency in generating high quality human insight data across a range of modalities, inclusive of text, image video and audio. - Capable of making sound judgments and logical decisions when faced with ambiguous or incomplete information while performing tasks. - Eye for detail and ability to pivot from one category of requirement to another instantaneously. - Demonstrate support on daily operational deliverables for multiple task types assigned to you and the team - Analyze root causes, identify error patterns, and propose solutions to enhance the quality of labeling tasks and their outputs. - Responsible for identifying day-to-day process and operational issues in Standard Operating Procedure, tools and suggest changes to unblock operations - Demonstrate ownership in floor support to clarify internal queries during execution on need basis A day in the life We are looking for a ML Data Associate (MLDA) to undertake the task of foundational labeling functions, such as dialogue evaluation on speech, text, audio, video data. Your ability to concentrate, multi-task and your high attention to detail helps you deliver high-quality work as well as maintaining strict confidentiality and follow all applicable Amazon policies for securing confidential information. You will be a part of a diverse team with the shared vision of improving customers’ lives with practical, useful generative AI innovations. An inner drive, individuality, and a creative mind are extremely beneficial. About the team The team works strictly in the office Monday through Friday. We are constantly looking for ways to improve our capabilities and deliver the best product possible. Diverse team, regular meetings, trainings, and Amazon events throughout the year await you. The minimum base pay salary for this position is listed below. As a total compensation company, Amazon's package may include further pay components such as performance bonuses, where applicable. Your recruiting team will share final base pay and any applicable total compensation elements depending on skills and requirements.Company discretionary, supplementary benefits apply subject to further terms, including pension plans, health insurance, life and disability insurance, business travel insurance, MultiSport card, employee discount code and program (EDC/Extras), commuter benefits where applicable, and the Employee Assistance Program (private and confidential counselling and referral service to support health and well-being).The minimum base pay for this position is PLN 7.916.66 monthly. Wynagrodzenie podstawowe dla tego stanowiska jest wskazane poniżej. Amazon kieruje się zasadą całkowitego wynagrodzenia, w związku z czym oprócz wynagrodzenia zasadniczego mogą być przewidziane dodatkowe składniki wynagrodzenia, takie jak premie (w odpowiednich przypadkach). Zespół rekrutacyjny poinformuje Cię o ostatecznej kwocie wynagrodzenia zasadniczego oraz o wszystkich przysługujących dodatkowych składnikach wynagrodzenia, w zależności od umiejętności i wymagań.Dodatkowe świadczenia przysługują na warunkach obowiązujących w Spółce i obejmują m.in. plany emerytalne, dodatkowe ubezpieczenie zdrowotne, dodatkowe ubezpieczenie na życie, ubezpieczenie podróży służbowych, kartę MultiSport, kod rabatowy dla pracowników i program zniżek pracowniczych (EDC/Extras), dotacje dla osób dojeżdżających (w odpowiednich przypadkach) oraz Program Wsparcia Pracownika (EAP – prywatne i poufne doradztwo i wsparcie).Wynagrodzenie podstawowe dla tego stanowiska wynosi 7,916.66 PLN miesięcznie. Basic Qualifications: - An Associate’s Degree or related work experience - - C1+ or equivalent fluency in French language - - Good working knowledge (B2+) in both spoken and written English - - Strong business writing skills with ability to create reports, proposals, and professional correspondence - - Advanced reading comprehension with ability to analyze complex business documents - - Developed analytical thinking and structured problem-solving capabilities - - Strong ability to interpret and implement detailed instructions across various projects - - Proficient research skills with experience gathering and synthesizing information from multiple sources - - Proven attention to detail in managing complex tasks and documents Preferred Qualifications: - Bachelor’s degree in a relevant field - 2+ years of professional work experience with demonstrated task execution ability - Proven capacity to leverage open-source resources effectively for comprehensive research purposes - Ability to adapt well to fast-paced environments with changing circumstances, direction, and strategy - 2-3 years project coordination or management experience (for support functions teams) - Experience managing stakeholder relationships across departments - Advanced proficiency in Microsoft Office Suite and common business applications. - - Bachelor’s degree in a relevant field - - 2+ years of professional work experience with demonstrated task execution ability - - Proven capacity to leverage open-source resources effectively for comprehensive research purposes - - Ability to adapt well to fast-paced environments with changing circumstances, direction, and strategy - - 2-3 years project coordination or management experience (for support functions teams) - - Experience managing stakeholder relationships across departments - - Advanced proficiency in Microsoft Office Suite and common business applications. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( https://www.amazon.jobs/en/privacy_page ) to know more about how we collect, use and transfer the personal data of our candidates. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.", "summaryDescription" : "AI Data Annotation Specialist (French) at Amazon MLS Poland Sp. z o.o. - K69. Skills: Data annotation, LLM development. Maintain strict confidentiality. Work with different data types", "postedDate" : "2026-06-13T04:28:02.969", "createdAt" : "2026-06-13T04:28:02.969", "lastUpdated" : "2026-06-14T23:54:59.758", "ingestTimestamp" : "2026-06-13T04:28:02.969", "mongoId" : "69c94a759bc74574cbbb3da1", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3191110/apply", "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ "Root cause analysis", "Error pattern identification", "Eye for detail", "Individuality", "Creative mind", "Data annotation", "LLM development", "Data labelling", "Dialogue evaluation", "Generative AI", "Large language models", "In-house tools" ], "skillCount" : 12, "jobCategory" : "operations", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a2c6ace74d8ee00a090e155", "title" : "Data Annotator", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 15000.0, "max" : 25000.0, "currency" : "BGN", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Entry-level Data Annotator compensation in Bulgaria, adjusted for a part-time remote role in the technology industry." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-16T05:15:03.250", "fingerprint" : "7ec94f33947c2d9ecc0224266f4047f6c4d3d59572c1bba505186556883a4928", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4235828009", "externalId" : "4235828009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Bulgaria", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "Bulgaria", "employmentType" : "PART_TIME", "minimumEducation" : "High School", "coreResponsibilities" : "Rate/assess AI model performance, Label content elements, Assign predefined categories or labels, Evaluate content quality/appropriateness, Generate labels for concept understanding, Create training data by transforming data, Review data and identify product feature function, Label model outputs, Order or rank items, Create prompts for AI systems, Evaluate content relevance, Generate responses to prompts, Rewrite existing text, Produce concise summaries, Convert spoken language to text, Convert content between languages, Gather and compile data for AI models", "domainKnowledge" : "Generative AI; Large language models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large language models" ], "qualificationsBasic" : "High School Diploma or higher, Professional or Expert level proficiency (C1/C2) in English", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Data Annotators to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A High School Diploma or higher is required. Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $13 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.", "summaryDescription" : "Data Annotator at Innodata Inc.. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T20:03:44.730", "createdAt" : "2026-06-14T20:03:44.730", "lastUpdated" : "2026-06-16T05:15:03.250", "ingestTimestamp" : "2026-06-14T20:03:44.730", "mongoId" : "6a2c6ace74d8ee00a090e155", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "<30k", "hasSalary" : false, "allSkills" : [ "Generative AI", "Large language models" ], "skillCount" : 2, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6ace74d8ee00a090e15f", "title" : "Data Annotator", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 31000.0, "max" : 45000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Data Annotator in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-16T00:35:22.109", "fingerprint" : "13d41f4e12f1d70197e75a5fc7205669e36c7b2ea9413cee46ee42c1e0c3e49a", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4232469009", "externalId" : "4232469009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "High School", "coreResponsibilities" : "Rate/assess AI model performance, Label content elements, Assign predefined categories or labels, Evaluate perceived quality/appropriateness of content, Generate labels to advance concept understanding, Create training data by applying transformations, Modify images (rotation, flipping, cropping), Generate new text (paraphrasing, summarization), Alter audio/video signals (speed modification, pitch shifting), Review data and identify product feature function, Label model outputs, Identify gaming, Identify branded content, Order or rank items based on criteria, Create prompts or questions for AI systems, Evaluate content relevance, Generate responses to prompts or questions, Rewrite existing text preserving original meaning, Produce concise summaries of text or data, Convert spoken language to written text, Convert text or spoken language from one language, Gather and compile data for AI models, Compile text, images, videos, audio files", "domainKnowledge" : "Generative AI; Large language models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large language models" ], "qualificationsBasic" : "High School Diploma or higher, Professional or Expert level proficiency (C1/C2) in English", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Data Annotators to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A High School Diploma or higher is required. Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $9 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.", "summaryDescription" : "Data Annotator at Innodata Inc.. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T20:02:39.234", "createdAt" : "2026-06-14T20:02:39.234", "lastUpdated" : "2026-06-16T00:35:22.109", "ingestTimestamp" : "2026-06-14T20:02:39.234", "mongoId" : "6a2c6ace74d8ee00a090e15f", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 31000, "salaryAnnualMax" : 45000, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Generative AI", "Large language models" ], "skillCount" : 2, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6ace74d8ee00a090e161", "title" : "Data Annotator", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 31000.0, "max" : 45000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry level Data Annotator in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-16T02:40:34.194", "fingerprint" : "05fbbbb7ef751e564376b00b473c03750f2b12f76b320024dccb9dd447601dd0", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4234822009", "externalId" : "4234822009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "High School", "coreResponsibilities" : "Rate/assess AI model performance, Label content elements, Assign predefined categories or labels, Evaluate perceived quality/appropriateness of content, Generate labels to advance concept understanding, Create training data by applying transformations, Modify images (rotation, flipping, cropping), Generate new text (paraphrasing, summarization), Alter audio/video signals (speed modification, pitch shifting), Review data and identify product feature function, Label model outputs, Identify gaming, Identify branded content, Order or rank items based on criteria, Create prompts for language models, Evaluate content relevance, Generate responses to prompts, Rewrite existing text, Produce concise summaries, Convert spoken language to text, Convert text from one language to another, Gather and compile data for AI models", "domainKnowledge" : "Generative AI; Large language models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large language models" ], "qualificationsBasic" : "High School Diploma or higher, Professional or Expert level proficiency (C1/C2) in English", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Data Annotators to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A High School Diploma or higher is required. Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $9 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.", "summaryDescription" : "Data Annotator at Innodata Inc.. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T19:57:50.206", "createdAt" : "2026-06-14T19:57:50.206", "lastUpdated" : "2026-06-16T02:40:34.194", "ingestTimestamp" : "2026-06-14T19:57:50.206", "mongoId" : "6a2c6ace74d8ee00a090e161", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 31000, "salaryAnnualMax" : 45000, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Generative AI", "Large language models" ], "skillCount" : 2, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6ace74d8ee00a090e160", "title" : "Data Annotator", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 31000.0, "max" : 45000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Data Annotator in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-16T04:34:14.360", "fingerprint" : "56ba0b2819dcc4bd5fa25a55bdc7318fe938c274db725c57cbc0f5012889d1d6", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4232330009", "externalId" : "4232330009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "High School", "coreResponsibilities" : "Rate/assess AI model performance, Label content elements, Assign predefined categories or labels, Evaluate content quality/appropriateness, Generate labels for concept understanding, Create training data by transforming data, Modify images (rotation, flipping, cropping), Generate new text (paraphrasing, summarization), Alter audio/video signals (speed, pitch), Review data and identify product feature function, Label model outputs, Identify gaming, Identify branded content, Order or rank items, Create prompts for AI systems, Evaluate content relevance, Generate responses to prompts, Rewrite text preserving original meaning, Produce concise summaries, Convert spoken language to text, Convert text/spoken language between languages, Gather and compile data for AI models", "domainKnowledge" : "Generative AI; Large language models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large language models" ], "qualificationsBasic" : "High School Diploma or higher, Professional or Expert level proficiency (C1/C2) in English", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Data Annotators to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A High School Diploma or higher is required. Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $9 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.", "summaryDescription" : "Data Annotator at Innodata Inc.. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T18:33:03.429", "createdAt" : "2026-06-14T18:33:03.429", "lastUpdated" : "2026-06-16T04:34:14.360", "ingestTimestamp" : "2026-06-14T18:33:03.429", "mongoId" : "6a2c6ace74d8ee00a090e160", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 31000, "salaryAnnualMax" : 45000, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Generative AI", "Large language models" ], "skillCount" : 2, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6ace74d8ee00a090e158", "title" : "Data Annotator", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 200000.0, "max" : 400000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an entry-level Data Annotator in India, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-15T09:50:36.888", "fingerprint" : "d478c716c3e8bf3d620c5c8b4707d98b57818f678461ca9d02823d48f0d530a3", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4235832009", "externalId" : "4235832009", "industryFunction" : { }, "structuredLocations" : [ { "workMode" : "remote" } ], "locationText" : "", "employmentType" : "PART_TIME", "minimumEducation" : "High School", "technicalSkills" : "Python, SQL, R, Scala, Spark, Dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, GCP, Azure", "professionalSkills" : [ "Data annotation", "Data labeling", "Content evaluation", "Data transformation", "Data review", "Data gathering", "Data compilation" ], "hardSkillsList" : [ "Statistical analysis", "Machine learning", "Natural language processing", "Data modeling", "Data engineering", "AI development" ], "hardSkills" : [ { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Natural language processing", "level" : "intermediate" }, { "name" : "Data modeling", "level" : "intermediate" }, { "name" : "Data engineering", "level" : "intermediate" }, { "name" : "AI development", "level" : "intermediate" } ], "majorSkills" : "Data Annotation, AI Development, LLM Training", "majorSkillsList" : [ "Data Annotation", "AI Development", "LLM Training" ], "coreResponsibilities" : "Rate/assess AI model performance, Label content elements, Assign predefined categories/labels, Evaluate content quality/appropriateness, Generate labels for concepts/trends, Create training data, Apply data transformations, Review data for product feature function, Label model outputs, Order or rank items, Create prompts for AI systems, Evaluate content relevance, Generate responses from AI systems, Rewrite existing text, Produce text summaries, Convert audio to text, Translate languages, Gather and compile data", "domainKnowledge" : "Generative AI; Large Language Models; AI systems; Data engineering; Natural language; Reasoning", "domainList" : [ "generative-ai", "large-language-models", "ai-systems", "data-engineering", "natural-language", "reasoning" ], "domainSpecificKnowledge" : [ "Generative AI", "Large Language Models", "AI systems", "Data engineering", "Natural language", "Reasoning" ], "toolProficiency" : [ "Generative AI", "Large Language Models" ], "qualificationsBasic" : "High School Diploma or higher, Professional or Expert level proficiency in English", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certs", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Data Annotator to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A High School Diploma or higher is required. Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $13 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.", "summaryDescription" : "Data Annotator at Innodata Inc.. Skills: Data Annotation, AI Development, LLM Training. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T07:57:51.692", "createdAt" : "2026-06-14T07:57:51.692", "lastUpdated" : "2026-06-15T09:50:36.888", "ingestTimestamp" : "2026-06-14T07:57:51.692", "mongoId" : "6a2c6ace74d8ee00a090e158", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Statistical analysis", "Machine learning", "Natural language processing", "Data modeling", "Data engineering", "AI development", "Data Annotation", "AI Development", "LLM Training", "Data annotation", "Data labeling", "Content evaluation", "Data transformation", "Data review", "Data gathering", "Data compilation", "Generative AI", "Large Language Models", "AI systems", "Natural language", "Reasoning", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "skillCount" : 25, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6ace74d8ee00a090e15b", "title" : "Data Annotator", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 240000.0, "max" : 480000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an entry-level Data Annotator in India, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T09:17:30.177", "fingerprint" : "933264fcf3b9b0510c8d9fffde21679e6dd178b2fa3065b3960ac09255e5a639", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4232190009", "externalId" : "4232190009", "industryFunction" : { }, "structuredLocations" : [ { "workMode" : "remote" } ], "locationText" : "", "employmentType" : "PART_TIME", "minimumEducation" : "High School", "technicalSkills" : "AI, Generative AI, Large Language Models, Machine Learning", "hardSkillsList" : [ "Data annotation", "Content labeling", "Data transformation", "Content evaluation", "Prompt creation", "Text summarization", "Transcription", "Translation", "Data gathering" ], "hardSkills" : [ { "name" : "Data annotation", "level" : "intermediate" }, { "name" : "Content labeling", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Content evaluation", "level" : "intermediate" }, { "name" : "Prompt creation", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Transcription", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" } ], "majorSkills" : "Data annotation, AI development, LLM training", "majorSkillsList" : [ "Data annotation", "AI development", "LLM training" ], "coreResponsibilities" : "Rate AI model performance, Label content elements, Assign predefined categories, Evaluate content quality, Generate labels for concepts, Create training data, Review data for product features, Label model outputs, Order or rank items, Create prompts for AI systems, Evaluate content relevance, Generate responses from AI, Rewrite existing text, Produce text summaries, Convert audio to text, Translate languages, Gather and compile data", "domainKnowledge" : "Generative AI; Large Language Models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large Language Models" ], "qualificationsBasic" : "High School Diploma or higher, Professional or Expert level proficiency in English", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Data Annotators to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A High School Diploma or higher is required. Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $9 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.", "summaryDescription" : "Data Annotator at Innodata Inc.. Skills: Data annotation, AI development, LLM training. Rate AI model performance. Label content elements", "postedDate" : "2026-06-14T02:47:49.071", "createdAt" : "2026-06-14T02:47:49.071", "lastUpdated" : "2026-06-15T09:17:30.177", "ingestTimestamp" : "2026-06-14T02:47:49.071", "mongoId" : "6a2c6ace74d8ee00a090e15b", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Data annotation", "Content labeling", "Data transformation", "Content evaluation", "Prompt creation", "Text summarization", "Transcription", "Translation", "Data gathering", "AI development", "LLM training", "Generative AI", "Large Language Models" ], "skillCount" : 13, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6ace74d8ee00a090e157", "title" : "Data Annotator", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 200000.0, "max" : 400000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an entry-level Data Annotator in India, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T09:32:57.004", "fingerprint" : "59a0e1b7fb106598bc6b2798b593af4e8dac15b77a499ece4ca1f8921f8723c9", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4231736009", "externalId" : "4231736009", "industryFunction" : { }, "structuredLocations" : [ { "workMode" : "remote" } ], "locationText" : "", "employmentType" : "PART_TIME", "minimumEducation" : "High School", "technicalSkills" : "AI, Generative AI, Large Language Models, Machine Learning", "hardSkillsList" : [ "Data annotation", "Content labeling", "Data transformation", "Data gathering", "Data compilation", "Text summarization", "Speech to text", "Translation" ], "hardSkills" : [ { "name" : "Data annotation", "level" : "intermediate" }, { "name" : "Content labeling", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" }, { "name" : "Data compilation", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Speech to text", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" } ], "majorSkills" : "Data Annotation, AI Development, LLM Training", "majorSkillsList" : [ "Data Annotation", "AI Development", "LLM Training" ], "coreResponsibilities" : "Rate AI model performance, Assess AI model behavior, Label content elements, Assign predefined categories, Evaluate content quality, Evaluate content appropriateness, Generate labels for concepts, Generate labels for trends, Create training data, Apply data transformations, Modify images, Generate new text, Alter audio/video signals, Review data, Identify product feature function, Label model outputs, Identify content type, Order items, Rank items, Create prompts for AI, Generate responses from AI, Rewrite existing text, Preserve original meaning, Produce concise summaries, Convert audio to text, Convert language to text, Gather data, Compile data", "domainKnowledge" : "Generative AI; Large Language Models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large Language Models" ], "qualificationsBasic" : "High School Diploma or higher, Professional or Expert level proficiency in English", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Data Annotators to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A High School Diploma or higher is required. Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $9 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.", "summaryDescription" : "Data Annotator at Innodata Inc.. Skills: Data Annotation, AI Development, LLM Training. Rate AI model performance. Assess AI model behavior", "postedDate" : "2026-06-14T01:44:26.636", "createdAt" : "2026-06-14T01:44:26.636", "lastUpdated" : "2026-06-15T09:32:57.004", "ingestTimestamp" : "2026-06-14T01:44:26.636", "mongoId" : "6a2c6ace74d8ee00a090e157", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Data annotation", "Content labeling", "Data transformation", "Data gathering", "Data compilation", "Text summarization", "Speech to text", "Translation", "Data Annotation", "AI Development", "LLM Training", "Generative AI", "Large Language Models" ], "skillCount" : 13, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2a660974d8ee00a062ba0b", "title" : "AI Data Trainer (Arabic)", "company" : "ADCI", "industry" : "Editorial, Writing, Content Management, Machine Learning Data Operatio, Retail", "salary" : { "min" : 600000.0, "max" : 900000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Junior AI Data Trainer in Gurugram, India, adjusted for the technology industry and full-time employment." }, "location" : "Gurugram, Haryana, IND", "locations" : [ "Gurugram, Haryana, IND" ], "certifications" : [ "Cambridge certifications" ], "timestamp" : "2026-06-15T06:29:26.031", "fingerprint" : "56b82498018ea2f6ba7b9128bcb5cc1c6e622f90eddd43b20bbf269fb0aebfd0", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10443291/apply", "externalId" : "abbd5398-299d-40a2-bf90-eb6cd3d4cdba", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Gurugram", "state" : "Haryana", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "28.4646148,77.0299194" } ], "locationText" : "Gurugram, Haryana, India", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 1, "technicalSkills" : "AI, LLMs, NLP", "professionalSkills" : [ "Content writing", "Editorial writing" ], "hardSkillsList" : [ "Arabic language proficiency" ], "softSkillsList" : [ "Analytical thinking", "Problem-solving" ], "hardSkills" : [ { "name" : "Arabic language proficiency", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Analytical thinking" }, { "name" : "Problem-solving" } ], "majorSkills" : "AI training, Data annotation, Arabic language", "majorSkillsList" : [ "AI training", "Data annotation", "Arabic language" ], "coreResponsibilities" : "Contribute to projects generating training datasets for AI, Create content generating text-based user input for AI, Validate data based on annotation guidelines, Perform data collection and curation, Generate high-quality data for AI models, Work closely with team members and managers, Drive process efficiencies, Explore opportunities for automation, Enhance productivity and effectiveness of data generation and", "teamCollaboration" : "Work closely with team members; Work with managers; Work with Shopping feature teams", "domainKnowledge" : "AI; LLMs; NLP; RLHF", "domainList" : [ "ai", "llms", "nlp", "rlhf" ], "domainSpecificKnowledge" : [ "AI", "LLMs", "NLP", "RLHF" ], "toolProficiency" : [ "Open AI" ], "communicationSkills" : "Written communication; Oral communication", "problemSolvingSkills" : "Analytical thinking; Problem-solving", "qualificationsBasic" : "Bachelor's degree in Arabic Language, 1+ years of experience in content or editorial writing, Proficient in Arabic language, Language proficiency in verbal, writing, reading and comprehension, Required language level: Graduation, Outstanding communication skills, Keen eye for detail, Organizational skills, Proficient in analytical thinking, Proficient in problem-solving", "qualificationsPreferred" : "Post Graduation degree in Arabic Language, Previous experience as AI trainers, Knowledge of AI and NLP, Cambridge certifications, Experience with Artificial Intelligence interaction, Prompt generation experience, Open AI's experience", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Alexa Shopping Operations strives to become the most reliable source for dataset generation and annotations. We work in collaboration with Shopping feature teams to enhance customer experience (CX) quality across shopping features, devices, and locales. Our primary focus lies in handling annotations for training, measuring, and improving Artificial Intelligence (AI) and Large Language Models (LLMs), enabling Amazon to deliver a superior shopping experience to customers worldwide. Our mission is to empower Amazon's LLMs through Reinforcement Learning from Human Feedback (RLHF) across various categories at high speed. We aspire to provide an end-to-end data solution for the LLM lifecycle, leveraging cutting-edge technology alongside our operational excellence. By joining us, you will play a pivotal role in shaping the future of the shopping experience for customers worldwide. Key job responsibilities As part of your role, you will have the opportunity to, • Contribute to various projects involved in generating training datasets for AI models • Create content that generates text-based user input to power artificial intelligence • Validate data based on specific annotation guidelines, ensuring the accuracy and quality of the collected information • Perform data collection and curation, ultimately resulting in the generation of high-quality data that can be utilized for AI models • You will work closely with your team members and managers to drive process efficiencies and explore opportunities for automation • You will strive to enhance the productivity and effectiveness of the data generation and annotation processes About the team Alexa Shopping Operations strives to become the most reliable source for dataset generation and annotations. We work in collaboration with Shopping feature teams to enhance customer experience (CX) quality across shopping features, devices, and locales. Our primary focus lies in handling annotations for training, measuring, and improving Artificial Intelligence (AI) and Large Language Models (LLMs), enabling Amazon to deliver a superior shopping experience to customers worldwide. Our mission is to empower Amazon's LLMs through Reinforcement Learning from Human Feedback (RLHF) across various categories at high speed. Basic Qualifications: - Bachelor's degree in Arabic Language - 1+ years of experience in content or editorial writing. - Proficient in Arabic language. - Candidate must demonstrate language proficiency in all the following: verbal, writing, reading and comprehension. - Required language level: Graduation - Outstanding communication skills, both written and oral, with a keen eye for detail. - Strong organizational skills to effectively manage tasks and projects. - Proficient in analytical thinking and problem-solving. - Comfortable working in a fast-paced, highly collaborative, and dynamic work environment. Preferred Qualifications: - Post Graduation degree in Arabic Language. - Previous experience as AI trainers, knowledge of AI and NLP, Cambridge certifications Experience with Artificial Intelligence interaction, such as prompt generation and open AI's Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.", "summaryDescription" : "AI Data Trainer (Arabic) at ADCI. Skills: AI training, Data annotation, Arabic language. Contribute to projects generating training datasets for AI. Create content generating text-based user input for AI", "postedDate" : "2026-06-13T09:52:33.242", "createdAt" : "2026-06-13T09:52:33.242", "lastUpdated" : "2026-06-15T06:29:26.031", "ingestTimestamp" : "2026-06-13T09:52:33.242", "mongoId" : "6a2a660974d8ee00a062ba0b", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10443291/apply", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Arabic language proficiency", "Analytical thinking", "Problem-solving", "AI training", "Data annotation", "Arabic language", "Content writing", "Editorial writing", "AI", "LLMs", "NLP", "RLHF", "Cambridge certifications", "Open AI" ], "skillCount" : 14, "jobCategory" : "engineering", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a2c6ace74d8ee00a090e15a", "title" : "Data Annotator", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 240000.0, "max" : 480000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an entry-level Data Annotator in India, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T06:46:26.516", "fingerprint" : "ca9feb2deb00ae1cb491b3dae921b1d080fa94e66bc6163e8e13fecaafe908ea", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4235831009", "externalId" : "4235831009", "industryFunction" : { }, "structuredLocations" : [ { "workMode" : "remote" } ], "locationText" : "", "employmentType" : "PART_TIME", "minimumEducation" : "High School", "technicalSkills" : "AI, Generative AI, Large Language Models, Machine Learning", "professionalSkills" : [ "Data annotation", "Content evaluation", "Data labeling", "Data transformation", "Content review", "Data gathering", "Data compilation", "Text summarization", "Speech to text", "Translation", "Prompt creation", "Response generation", "Text rewriting" ], "hardSkillsList" : [ "Language intricacies", "Reasoning" ], "hardSkills" : [ { "name" : "Language intricacies", "level" : "intermediate" }, { "name" : "Reasoning", "level" : "intermediate" } ], "majorSkills" : "Data annotation, AI development", "majorSkillsList" : [ "Data annotation", "AI development" ], "coreResponsibilities" : "Rate AI model performance, Assess AI model behavior, Label content elements, Assign predefined categories, Evaluate content quality, Evaluate content appropriateness, Generate labels for concepts, Generate labels for trends, Create training data, Apply data transformations, Modify images, Generate new text, Alter audio/video signals, Review data for product features, Identify product feature function, Label model outputs, Identify content type, Order items by criteria, Rank items by criteria, Create prompts for AI, Generate responses from AI, Rewrite existing text, Preserve original meaning, Improve text clarity, Improve text style, Produce text summaries, Produce data summaries, Convert audio to text, Translate content, Gather digital content, Compile digital content", "domainKnowledge" : "Generative AI; Large Language Models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large Language Models" ], "qualificationsBasic" : "High School Diploma or higher, Professional or Expert level proficiency in English", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Data Annotators to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A High School Diploma or higher is required. Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $13 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.", "summaryDescription" : "Data Annotator at Innodata Inc.. Skills: Data annotation, AI development. Rate AI model performance. Assess AI model behavior", "postedDate" : "2026-06-13T20:43:22.195", "createdAt" : "2026-06-13T20:43:22.195", "lastUpdated" : "2026-06-15T06:46:26.516", "ingestTimestamp" : "2026-06-13T20:43:22.195", "mongoId" : "6a2c6ace74d8ee00a090e15a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Language intricacies", "Reasoning", "Data annotation", "AI development", "Content evaluation", "Data labeling", "Data transformation", "Content review", "Data gathering", "Data compilation", "Text summarization", "Speech to text", "Translation", "Prompt creation", "Response generation", "Text rewriting", "Generative AI", "Large Language Models" ], "skillCount" : 18, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6ace74d8ee00a090e156", "title" : "Data Annotator", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 200000.0, "max" : 400000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an entry-level Data Annotator in India, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T11:07:30.384", "fingerprint" : "c2fc1fdc7bc454b442c6fe16fe6bb4624209a7515a4285a5798d21e39a48d3dc", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4235827009", "externalId" : "4235827009", "industryFunction" : { }, "structuredLocations" : [ { "workMode" : "remote" } ], "locationText" : "", "employmentType" : "PART_TIME", "minimumEducation" : "High School", "technicalSkills" : "AI, Generative AI, Large Language Models, Machine Learning", "professionalSkills" : [ "Data engineering", "Evaluation frameworks", "Human expertise" ], "hardSkillsList" : [ "Data annotation", "Content labeling", "Data transformation", "Data gathering", "Data compilation", "Text summarization", "Speech to text", "Translation" ], "hardSkills" : [ { "name" : "Data annotation", "level" : "intermediate" }, { "name" : "Content labeling", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" }, { "name" : "Data compilation", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Speech to text", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" } ], "majorSkills" : "Data annotation, AI development, Language understanding", "majorSkillsList" : [ "Data annotation", "AI development", "Language understanding" ], "coreResponsibilities" : "Rate AI model performance, Assess AI model behavior, Label content elements, Assign predefined categories, Evaluate content quality, Evaluate content appropriateness, Generate labels for concepts, Generate labels for trends, Create training data, Apply data transformations, Modify images, Generate new text, Alter audio/video signals, Review data, Identify product feature function, Label model outputs, Identify content presence, Order items, Rank items, Create prompts for AI, Generate responses from AI, Rewrite existing text, Preserve original meaning, Produce concise summaries, Convert audio to text, Convert language to text, Gather data, Compile data", "domainKnowledge" : "Generative AI; Large Language Models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large Language Models" ], "outcomesObjectives" : "Build AI systems at scale; Advance AI responsibly", "qualificationsBasic" : "High School Diploma or higher, Professional or Expert level proficiency in English", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Data Annotators to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A High School Diploma or higher is required. Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $13 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.", "summaryDescription" : "Data Annotator at Innodata Inc.. Skills: Data annotation, AI development, Language understanding. Rate AI model performance. Assess AI model behavior", "postedDate" : "2026-06-13T20:08:26.994", "createdAt" : "2026-06-13T20:08:26.994", "lastUpdated" : "2026-06-15T11:07:30.384", "ingestTimestamp" : "2026-06-13T20:08:26.994", "mongoId" : "6a2c6ace74d8ee00a090e156", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Data annotation", "Content labeling", "Data transformation", "Data gathering", "Data compilation", "Text summarization", "Speech to text", "Translation", "AI development", "Language understanding", "Data engineering", "Evaluation frameworks", "Human expertise", "Generative AI", "Large Language Models" ], "skillCount" : 15, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2a660974d8ee00a062ba0a", "title" : "Data Associate (Arabic), Alexa Shopping Operations", "company" : "ADCI", "industry" : "Editorial, Writing, Content Management, Machine Learning Data Operatio, Retail", "salary" : { "min" : 550000.0, "max" : 850000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for an Entry-level Data Associate in the Technology industry in Gurugram, India, adjusted for company size and specific role requirements." }, "location" : "Gurugram, Haryana, IND", "locations" : [ "Gurugram, Haryana, IND" ], "certifications" : [ "Cambridge certifications" ], "timestamp" : "2026-06-15T07:24:02.908", "fingerprint" : "85d83cef02c73c8a6db90923b6aad14a7a36f53e0485c4cf367e72a06b1a936c", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10443292/apply", "externalId" : "26d60c99-8ac8-452d-8858-18391a49b235", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Gurugram", "state" : "Haryana", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "28.4646148,77.0299194" } ], "locationText" : "Gurugram, Haryana, India", "employmentType" : "FULL_TIME", "minimumEducation" : "Graduate", "experienceMinYears" : 0, "experienceMaxYears" : 1, "experienceLevel" : "Entry", "technicalSkills" : "AI, LLMs, NLP", "hardSkillsList" : [ "Data collection", "Data curation", "Annotation guidelines" ], "hardSkills" : [ { "name" : "Data collection", "level" : "intermediate" }, { "name" : "Data curation", "level" : "intermediate" }, { "name" : "Annotation guidelines", "level" : "intermediate" } ], "majorSkills" : "Data annotation, AI training, LLM development", "majorSkillsList" : [ "Data annotation", "AI training", "LLM development" ], "coreResponsibilities" : "Contribute to projects generating training datasets, Create content generating text-based user input, Validate data based on annotation guidelines, Perform data collection and curation, Generate high-quality data for AI models, Work closely with team members, Drive process efficiencies, Explore opportunities for automation, Enhance productivity of data generation, Enhance annotation processes", "teamCollaboration" : "Work with Shopping feature teams; Collaborate with team members; Collaborative work environment", "domainKnowledge" : "Artificial Intelligence; Large Language Models; Shopping experience", "domainList" : [ "artificial-intelligence", "large-language-models", "shopping-experience" ], "domainSpecificKnowledge" : [ "Artificial Intelligence", "Large Language Models", "Shopping experience" ], "communicationSkills" : "Written communication; Oral communication", "problemSolvingSkills" : "Analytical thinking; Problem-solving", "qualificationsBasic" : "Graduate or equivalent, Proficient in Arabic language, Demonstrate language proficiency, Outstanding communication skills, Organizational skills, Analytical thinking, Problem-solving", "qualificationsPreferred" : "Post Graduation degree in Arabic Language, Previous experience as AI trainers, Knowledge of AI and NLP, Cambridge certifications, Experience with AI interaction, Prompt generation, Open AI's", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Alexa Shopping Operations strives to become the most reliable source for dataset generation and annotations. We work in collaboration with Shopping feature teams to enhance customer experience (CX) quality across shopping features, devices, and locales. Our primary focus lies in handling annotations for training, measuring, and improving Artificial Intelligence (AI) and Large Language Models (LLMs), enabling Amazon to deliver a superior shopping experience to customers worldwide. Our mission is to empower Amazon's LLMs through Reinforcement Learning from Human Feedback (RLHF) across various categories at high speed. We aspire to provide an end-to-end data solution for the LLM lifecycle, leveraging cutting-edge technology alongside our operational excellence. By joining us, you will play a pivotal role in shaping the future of the shopping experience for customers worldwide. Key job responsibilities As part of your role, you will have the opportunity to, • Contribute to various projects involved in generating training datasets for AI models • Create content that generates text-based user input to power artificial intelligence • Validate data based on specific annotation guidelines, ensuring the accuracy and quality of the collected information • Perform data collection and curation, ultimately resulting in the generation of high-quality data that can be utilized for AI models • You will work closely with your team members and managers to drive process efficiencies and explore opportunities for automation • You will strive to enhance the productivity and effectiveness of the data generation and annotation processes About the team Alexa Shopping Operations strives to become the most reliable source for dataset generation and annotations. We work in collaboration with Shopping feature teams to enhance customer experience (CX) quality across shopping features, devices, and locales. Our primary focus lies in handling annotations for training, measuring, and improving Artificial Intelligence (AI) and Large Language Models (LLMs), enabling Amazon to deliver a superior shopping experience to customers worldwide. Our mission is to empower Amazon's LLMs through Reinforcement Learning from Human Feedback (RLHF) across various categories at high speed. Basic Qualifications: - Graduate or equivalent (up to 1 year of experience). - Proficient in Arabic language. - Candidate must demonstrate language proficiency in all the following: verbal, writing, reading and comprehension. - Required language level: Graduation - Outstanding communication skills, both written and oral, with a keen eye for detail. - Strong organizational skills to effectively manage tasks and projects. - Proficient in analytical thinking and problem-solving. - Comfortable working in a fast-paced, highly collaborative, and dynamic work environment. Preferred Qualifications: - Post Graduation degree in Arabic Language. - Previous experience as AI trainers, knowledge of AI and NLP, Cambridge certifications Experience with Artificial Intelligence interaction, such as prompt generation and open AI's Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.", "summaryDescription" : "Data Associate (Arabic), Alexa Shopping Operations at ADCI. Skills: Data annotation, AI training, LLM development. Contribute to projects generating training datasets. Create content generating text-based user input", "postedDate" : "2026-06-14T01:43:38.222", "createdAt" : "2026-06-14T01:43:38.222", "lastUpdated" : "2026-06-15T07:24:02.908", "ingestTimestamp" : "2026-06-14T01:43:38.222", "mongoId" : "6a2a660974d8ee00a062ba0a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10443292/apply", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Data collection", "Data curation", "Annotation guidelines", "Data annotation", "AI training", "LLM development", "Artificial Intelligence", "Large Language Models", "Shopping experience", "Cambridge certifications" ], "skillCount" : 10, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a3087a4f292fd229c08b218", "title" : "Business Architect - Arabic Speaker", "company" : "Capco", "industry" : "Consulting", "salary" : { "min" : 350000.0, "max" : 550000.0, "currency" : "SAR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Business Architect in Riyadh, Saudi Arabia, adjusted for the consulting industry and company size." }, "location" : "Middle East - Riyadh", "locations" : [ "Middle East - Riyadh" ], "certifications" : [ "Business Architecture certification", "Enterprise Architecture certification", "Change Management certification" ], "timestamp" : "2026-06-16T11:43:17.498", "fingerprint" : "e39c4196ad4fc104f5de553aa53a4bedfbafa21ca26b08914ea128e32c0a30d0", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/capco/jobs/8007379", "externalId" : "8007379", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Riyadh", "country" : "Saudi Arabia", "continent" : "as", "source" : "llm", "workMode" : "hybrid", "geo" : "24.6389160,46.7160104" } ], "locationText" : "Riyadh, Saudi Arabia", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "professionalSkills" : [ "Stakeholder management", "Executive presentation" ], "hardSkillsList" : [ "Business capability mapping", "Target operating models", "Value streams", "Enterprise business architecture" ], "hardSkills" : [ { "name" : "Business capability mapping", "level" : "intermediate" }, { "name" : "Target operating models", "level" : "intermediate" }, { "name" : "Value streams", "level" : "intermediate" }, { "name" : "Enterprise business architecture", "level" : "intermediate" } ], "majorSkills" : "Business architecture, Enterprise transformation, Operating model design", "majorSkillsList" : [ "Business architecture", "Enterprise transformation", "Operating model design" ], "coreResponsibilities" : "Develop Business Capability Maps, Maintain Business Capability Maps, Develop Target Operating Models, Maintain Target Operating Models, Develop value streams, Maintain value streams, Develop enterprise business architecture artefacts, Maintain enterprise business architecture artefacts, Translate business strategy into services, Translate business strategy into governance frameworks, Translate business strategy into transformation roadmaps, Lead transformation initiatives, Align business teams, Align operations teams, Align product teams, Align technology teams, Identify capability gaps, Identify operational dependencies, Identify opportunities for innovation, Identify opportunities for scalability, Identify opportunities for efficiency improvements, Establish business architecture standards, Govern business architecture standards, Establish business architecture methodologies, Govern business architecture methodologies, Establish business architecture practices, Govern business architecture practices", "teamCollaboration" : "Cross-functional transformation initiatives; Aligning business, operations, product, technology", "projectManagementSkills" : [ "Transformation roadmaps" ], "domainKnowledge" : "Financial services; Capital markets; Wealth management; Digital financial services; Brokerage operating models", "domainList" : [ "financial-services", "capital-markets", "wealth-management", "digital-financial-services", "brokerage-operating-models" ], "domainSpecificKnowledge" : [ "Financial services", "Capital markets", "Wealth management", "Digital financial services", "Brokerage operating models" ], "communicationSkills" : "Executive presentation", "continuousLearning" : "Industry certifications", "innovationCreativity" : "Business innovation", "problemSolvingSkills" : "Identify capability gaps; Identify operational dependencies", "outcomesObjectives" : "Build scalable organizations; Build future-ready organizations; Enable informed decision-making; Drive sustainable business change; Achieve sustainable growth", "qualificationsBasic" : "Proven experience as Business Architect, Enterprise Architect experience, Strategic transformation role experience, Financial services experience, Arabic fluency", "qualificationsPreferred" : "Experience supporting large-scale transformation programmes, Knowledge of industry-standard business architecture frameworks, Knowledge of capability modelling methodologies, Experience working within complex financial services organizations, Exposure to digital transformation, Exposure to platform modernization, Exposure to operating model redesign initiatives, Professional certifications in Business Architecture, Professional certifications in Enterprise Architecture, Professional certifications in Change Management", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Please note we are looking to speak to individuals already based in the Riyadh as a first priority - please clearly state your location and fluency in Arabic on your CV. Candidates who state their location and fluency in Arabic will be prioritised. Capco, a Wipro company, is a global technology and management consultancy specializing in driving digital transformation in the financial services industry. With a growing client portfolio comprising of over 100 global organizations, Capco operates at the intersection of business and technology by combining innovative thinking with unrivalled industry knowledge to deliver end-to-end data-driven solutions and fast-track digital initiatives for banking and payments, capital markets, wealth and asset management, insurance, and the energy sector. Capco’s cutting-edge ingenuity is brought to life through its Innovation Labs and award-winning Be Yourself At Work culture and diverse talent. Business Architect Location: Riyadh (Hybrid) | Practice Area: Capital Markets | Type: Permanent Shape the future of financial services by connecting business strategy, operating models, and enterprise transformation. The Role Capco is seeking an experienced Business Architect to support strategic transformation initiatives across capital markets, wealth management, and digital financial services. This role sits at the intersection of business strategy, operating model design, and enterprise transformation, helping clients build scalable, future-ready organizations. You will work closely with senior stakeholders to establish enterprise-wide visibility of business capabilities, value streams, operating models, and organizational dependencies. By translating strategic objectives into practical business architecture frameworks, you will enable informed decision-making and drive sustainable business change. What You’ll Do Develop and maintain Business Capability Maps, Target Operating Models, value streams, and enterprise business architecture artefacts across investment and wealth management functions. Translate business strategy into structured business architecture services, governance frameworks, and transformation roadmaps. Lead cross-functional transformation initiatives, aligning business, operations, product, and technology teams around common objectives. Identify capability gaps, operational dependencies, and opportunities for business innovation, scalability, and efficiency improvements. Establish and govern business architecture standards, methodologies, and practices to support enterprise-wide transformation initiatives. What We’re Looking For Proven experience as a Business Architect, Enterprise Architect, or similar strategic transformation role within financial services. Strong understanding of brokerage, wealth management, capital markets, and digital financial services operating models. Experience designing enterprise business architecture artefacts, including capability maps, target operating models, governance frameworks, and value streams. Exceptional stakeholder management, communication, and executive presentation skills, with the ability to influence senior leadership. Demonstrated ability to drive business transformation initiatives and institutionalize knowledge into scalable frameworks and operating practices. Bonus Points For Experience supporting large-scale transformation programmes within investment banking, capital markets, or wealth management organizations. Knowledge of industry-standard business architecture frameworks and capability modelling methodologies. Experience working within complex, multi-entity or regional financial services organizations. Exposure to digital transformation, platform modernization, or operating model redesign initiatives. Professional certifications in Business Architecture, Enterprise Architecture, Change Management, or related disciplines. Why Join Capco Deliver high-impact transformation solutions for leading financial institutions across the Middle East and globally. Work in a collaborative, flat, and entrepreneurial consulting culture. Access continuous learning, training, and industry certifications. Be part of a team shaping the future of digital financial services. Help clients accelerate business transformation and achieve sustainable growth. Why This Role Is Open We are currently hiring for this role due to an existing or newly created vacancy within our organization. This position is open as part of our ongoing business needs, and we are actively reviewing applications to fill this role with a qualified candidate who can make an immediate impact. Inclusion at Capco We’re committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know – we’ll be happy to help. We value each person’s unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our #BeYourselfAtWork culture encourages individuality and collaboration – a mindset that shapes how we work with clients and each other every day.", "summaryDescription" : "Business Architect - Arabic Speaker at Capco. Skills: Business architecture, Enterprise transformation, Operating model design. Develop Business Capability Maps. Maintain Business Capability Maps", "postedDate" : "2026-06-16T01:21:48.717", "createdAt" : "2026-06-16T01:21:48.717", "lastUpdated" : "2026-06-16T11:43:17.498", "ingestTimestamp" : "2026-06-16T01:21:48.717", "mongoId" : "6a3087a4f292fd229c08b218", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Business capability mapping", "Target operating models", "Value streams", "Enterprise business architecture", "Business architecture", "Enterprise transformation", "Operating model design", "Stakeholder management", "Executive presentation", "Transformation roadmaps", "Financial services", "Capital markets", "Wealth management", "Digital financial services", "Brokerage operating models", "Business Architecture certification", "Enterprise Architecture certification", "Change Management certification" ], "skillCount" : 18, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Consulting", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e153", "title" : "Data AI Annotator", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 31000.0, "max" : 45000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Data AI Annotator in the US, adjusted for remote work and the technology industry." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T09:02:51.954", "fingerprint" : "f28a631641bd897018ea514eeb1e755b97e8bb9aaffee61813c50eedd793835e", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4266784009", "externalId" : "4266784009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "Generative AI, Large Language Models, Machine Learning", "professionalSkills" : [ "Data engineering", "AI development" ], "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Prompt creation", "Text summarization", "Translation", "Data gathering", "Data compilation" ], "hardSkills" : [ { "name" : "Data labeling", "level" : "intermediate" }, { "name" : "Content evaluation", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Prompt creation", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" }, { "name" : "Data compilation", "level" : "intermediate" } ], "majorSkills" : "Generative AI, LLM development, Data annotation", "majorSkillsList" : [ "Generative AI", "LLM development", "Data annotation" ], "coreResponsibilities" : "Rate AI model performance, Label content elements, Assign predefined categories, Evaluate content quality, Generate labels for concepts, Create training data, Review data for product features, Label model outputs, Order or rank items, Create prompts for AI systems, Evaluate content relevance, Generate responses to prompts, Rewrite existing text, Produce concise summaries, Convert audio to text, Translate content, Gather and compile data", "domainKnowledge" : "Artificial Intelligence; Large Language Models", "domainList" : [ "artificial-intelligence", "large-language-models" ], "domainSpecificKnowledge" : [ "Artificial Intelligence", "Large Language Models" ], "qualificationsBasic" : "Bachelor's degree or higher, Professional or Expert level proficiency in English", "qualificationsPreferred" : "Advanced degrees strongly preferred, Master's or PhD preferred", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Generative AI Specialist to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A Bachelor’s degree or higher in a humanities specialization is required. Advanced degrees are strongly preferred (Master’s or PhD) Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $15 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.", "summaryDescription" : "Data AI Annotator at Innodata Inc.. Skills: Generative AI, LLM development, Data annotation. Rate AI model performance. Label content elements", "postedDate" : "2026-06-14T02:56:15.234", "createdAt" : "2026-06-14T02:56:15.234", "lastUpdated" : "2026-06-15T09:02:51.954", "ingestTimestamp" : "2026-06-14T02:56:15.234", "mongoId" : "6a2c6ace74d8ee00a090e153", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 31000, "salaryAnnualMax" : 45000, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Prompt creation", "Text summarization", "Translation", "Data gathering", "Data compilation", "Generative AI", "LLM development", "Data annotation", "Data engineering", "AI development", "Artificial Intelligence", "Large Language Models" ], "skillCount" : 15, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "68c2e420f8b1b0376634c4b4", "title" : "Catalog Specialist, WWRR Science Annotation Team", "company" : "ADCI HYD 13 SEZ", "industry" : "Fulfillment Operations Management, Catalog, Retail", "salary" : { "min" : 850000.0, "max" : 1300000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Catalog Specialist in Hyderabad, India, adjusted for the E-commerce industry and company size." }, "location" : "Hyderabad, Telangana, IND", "locations" : [ "Hyderabad, Telangana, IND" ], "timestamp" : "2026-06-15T00:52:44.849", "fingerprint" : "ed87536216a796877c5456d69ab5605c062151c382e32b54401827f22e7358a0", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3078240/apply", "externalId" : "3c45ddd2-049f-4182-b0ff-b7a5a1c9b951", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Hyderabad", "state" : "Telangana", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "17.3605890,78.4740613" } ], "locationText" : "Hyderabad, Telangana, India", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 1, "experienceMaxYears" : 5, "experienceLevel" : "Mid", "technicalSkills" : "Machine Learning, ML models, Classification algorithms", "professionalSkills" : [ "Data annotation", "ML model training", "ML model evaluation" ], "hardSkillsList" : [ "Data annotation", "Classification algorithms" ], "softSkillsList" : [ "Leadership", "Problem-solving skills" ], "hardSkills" : [ { "name" : "Data annotation", "level" : "intermediate" }, { "name" : "Classification algorithms", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Problem-solving skills" } ], "majorSkills" : "Data annotation, ML models", "majorSkillsList" : [ "Data annotation", "ML models" ], "coreResponsibilities" : "Support Machine Learning (ML) models, Perform data annotation, Train ML models, Evaluate ML models, Support data scientists, Develop classification algorithms, Collaborate with cross-functional teams, Ensure data annotation tasks align with project objectives, Ensure data annotation tasks align with project timelines, Maintain high-quality standards for annotated data, Optimize model performance, Continuously evaluate annotation processes, Improve annotation processes, Enhance efficiency, Enhance accuracy", "teamCollaboration" : "Cross-functional teams; Product teams; Technology teams; Science teams", "projectManagementSkills" : [ "Time management", "Organization" ], "domainKnowledge" : "Reverse logistics processes; Machine learning concepts; ML algorithms", "domainList" : [ "reverse-logistics-processes", "machine-learning-concepts", "ml-algorithms" ], "domainSpecificKnowledge" : [ "Reverse logistics processes", "Machine learning concepts", "ML algorithms" ], "toolProficiency" : [ "Microsoft Office" ], "innovationCreativity" : "Innovate", "problemSolvingSkills" : "Deep-dive on complex problems; Problem-solving skills", "specialRequirements" : "German language proficiency", "outcomesObjectives" : "Delight customers through new experiences", "qualificationsBasic" : "Bachelor's degree, Speak, write, and read fluently in Spanish, Experience with Microsoft Office products and applications, 1+ years of proven experience in data annotation and labeling for ML model training and evaluation, Minimum B2 Language Proficiency required", "qualificationsPreferred" : "Experience working on the MTurk platform for data annotation tasks, Proven experience in data annotation and labeling for ML model training and evaluation, Understanding of data annotation methodologies and tools, Familiarity with Amazon's product and category ecosystem, Previous exposure to machine learning concepts and algorithms, Demonstrated ability to adapt to evolving technologies and methodologies in the ML domain", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "In the Worldwide Returns, ReCommerce & Sustainability (WW RR&S) group at Amazon, we are dedicated to ‘making zero happen’ – zero cost of returns, zero waste, and zero defects – to benefit our customers, company, and environment. We are an agile and inclusive organization that constantly innovates to create long-term value by investing in our people and our planet, not simply focusing on the bottom line. WW R&R includes business, product, operations, data, and software engineering teams, who together manage the lifecycle of returned and damaged products. In WW R&R, you will partner across these teams to help customers discover great deals on quality used, rentals, and open box items; get the most value out of Amazon’s products; improve the customer returns experience; and reduce defects, waste, and cost in reverse logistics processes. You will be a leader, a builder, and an owner, collaborating cross-functionally with technical, operations, and business teams to design scalable and automated solutions to customer problems. Amazon is Earth’s most customer-centric company and in WW R&R, the Earth is our customer too. Come join us and innovate with the Amazon Worldwide Returns, ReCommerce & Sustainability team! We are hiring an experienced Catalog Specialist to help us grow our business in innovative ways. In this role, you will work closely with our product, technology and science teams to support new Machine Learning (ML) models and data science classification algorithm development – all helping to delight our customers through new experiences throughout their Amazon shopping journey. Need candidates in language proficiency in: German Key job responsibilities • Work closely with our product, technology, and science teams to support Machine Learning (ML) models • Perform data annotation required to train and evaluate ML models effectively • Support data scientists in the development of classification algorithms • Collaborate with cross-functional teams to ensure data annotation tasks align with project objectives and timelines • Maintain high-quality standards for annotated data to optimize model performance • Continuously evaluate and improve annotation processes to enhance efficiency and accuracy • Strong analytical skills and the ability to deep-dive on complex problems • Ability to manage multiple simultaneous projects requiring frequent communication, organization/time management and problem-solving skills Basic Qualifications: Bachelor's degree Speak, write, and read fluently in Spanish Experience with Microsoft Office products and applications 1+ years of proven experience in data annotation and labeling for ML model training and evaluation Minimum B2 Language Proficiency required Preferred Qualifications: Experience working on the MTurk platform for data annotation tasks Proven experience in data annotation and labeling for ML model training and evaluation Understanding of data annotation methodologies and tools Familiarity with Amazon's product and category ecosystem Previous exposure to machine learning concepts and algorithms Demonstrated ability to adapt to evolving technologies and methodologies in the ML domain Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.", "summaryDescription" : "Catalog Specialist, WWRR Science Annotation Team at ADCI HYD 13 SEZ. Skills: Data annotation, ML models. Support Machine Learning (ML) models. Perform data annotation", "postedDate" : "2026-06-13T09:44:58.270", "createdAt" : "2026-06-13T09:44:58.270", "lastUpdated" : "2026-06-15T00:52:44.849", "ingestTimestamp" : "2026-06-13T09:44:58.270", "mongoId" : "68c2e420f8b1b0376634c4b4", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3078240/apply", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Data annotation", "Classification algorithms", "Leadership", "Problem-solving skills", "ML models", "ML model training", "ML model evaluation", "Time management", "Organization", "Reverse logistics processes", "Machine learning concepts", "ML algorithms", "Microsoft Office" ], "skillCount" : 13, "jobCategory" : "operations", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "69e1b5d82beec4dd3d1ac3fb", "title" : "Catalog Specialist, WWRR Science Annotation Team", "company" : "Amazon", "industry" : "Fulfillment Operations Management, Catalog, Retail", "salary" : { "min" : 1200000.0, "max" : 1800000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for a Mid-level Catalog Specialist in E-Commerce in Hyderabad, India, adjusted for Amazon's company size and industry." }, "location" : "Hyderabad, Telangana, IND", "locations" : [ "Hyderabad, Telangana, IND" ], "timestamp" : "2026-06-15T04:43:01.861", "fingerprint" : "597317e76471f47eb3d28b5c056372f14ed3a9cafd75b76197623ea199a31bf7", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/10382953/apply", "externalId" : "79163bdb-6071-48f2-8a8a-ba97e691e5cb", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Hyderabad", "state" : "Telangana", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "17.3605890,78.4740613" } ], "locationText" : "Hyderabad, Telangana, India", "employmentType" : "FULL_TIME", "technicalSkills" : "Machine Learning, ML models, Classification algorithms", "professionalSkills" : [ "Data annotation", "Annotation processes" ], "hardSkillsList" : [ "Analytical skills", "Problem-solving skills", "Time management skills" ], "hardSkills" : [ { "name" : "Analytical skills", "level" : "intermediate" }, { "name" : "Problem-solving skills", "level" : "intermediate" }, { "name" : "Time management skills", "level" : "intermediate" } ], "majorSkills" : "Data annotation, ML models", "majorSkillsList" : [ "Data annotation", "ML models" ], "coreResponsibilities" : "Work closely with product, technology, and science teams, Perform data annotation required to train and evaluate, Support data scientists in the development of classification, Collaborate with cross-functional teams to ensure data annotation, Maintain high-quality standards for annotated data to optimize, Continuously evaluate and improve annotation processes to enhance", "teamCollaboration" : "Cross-functional teams", "projectManagementSkills" : [ "Manage multiple simultaneous projects" ], "domainKnowledge" : "Reverse logistics processes; ML domain", "domainList" : [ "reverse-logistics-processes", "ml-domain" ], "domainSpecificKnowledge" : [ "Reverse logistics processes", "ML domain" ], "innovationCreativity" : "Innovate with the Amazon Worldwide Returns, ReCommerce & Sustainability team", "problemSolvingSkills" : "Deep-dive on complex problems", "qualificationsBasic" : "Minimum B2 Level certification in German Language, Spanish language proficiency", "qualificationsPreferred" : "Bachelor's degree or above in computer science, computer engineering, or related field, Experience in communicating technically, Proven experience in data annotation and labeling for ML model training and evaluation, Demonstrated ability to adapt to evolving technologies and methodologies in the ML domain", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "In the Worldwide Returns, ReCommerce & Sustainability (WW RR&S) group at Amazon, we are dedicated to ‘making zero happen’ – zero cost of returns, zero waste, and zero defects – to benefit our customers, company, and environment. We are an agile and inclusive organization that constantly innovates to create long-term value by investing in our people and our planet, not simply focusing on the bottom line. WW R&R includes business, product, operations, data, and software engineering teams, who together manage the lifecycle of returned and damaged products. In WW R&R, you will partner across these teams to help customers discover great deals on quality used, rentals, and open box items; get the most value out of Amazon’s products; improve the customer returns experience; and reduce defects, waste, and cost in reverse logistics processes. You will be a leader, a builder, and an owner, collaborating cross-functionally with technical, operations, and business teams to design scalable and automated solutions to customer problems. Amazon is Earth’s most customer-centric company and in WW R&R, the Earth is our customer too. Come join us and innovate with the Amazon Worldwide Returns, ReCommerce & Sustainability team! We are hiring an experienced Catalog Specialist to help us grow our business in innovative ways. In this role, you will work closely with our product, technology and science teams to support new Machine Learning (ML) models and data science classification algorithm development – all helping to delight our customers through new experiences throughout their Amazon shopping journey. Need candidates in language proficiency in: Spanish Key job responsibilities • Work closely with our product, technology, and science teams to support Machine Learning (ML) models • Perform data annotation required to train and evaluate ML models effectively • Support data scientists in the development of classification algorithms • Collaborate with cross-functional teams to ensure data annotation tasks align with project objectives and timelines • Maintain high-quality standards for annotated data to optimize model performance • Continuously evaluate and improve annotation processes to enhance efficiency and accuracy • Strong analytical skills and the ability to deep-dive on complex problems • Ability to manage multiple simultaneous projects requiring frequent communication, organization/time management and problem-solving skills Basic Qualifications: - Basic qualifications - Minimum B2 Level certification is mandatory in German Language Preferred Qualifications: - Preferred qualifications - Bachelor's degree or above in computer science, computer engineering, or related field, or experience in communicating technically, at a level appropriate for the audience - Proven experience in data annotation and labeling for ML model training and evaluation - Demonstrated ability to adapt to evolving technologies and methodologies in the ML domain Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.", "summaryDescription" : "Catalog Specialist, WWRR Science Annotation Team at Amazon. Skills: Data annotation, ML models. Work closely with product, technology, and science teams. Perform data annotation required to train and evaluate", "postedDate" : "2026-06-13T10:35:05.241", "createdAt" : "2026-06-13T10:35:05.241", "lastUpdated" : "2026-06-15T04:43:01.861", "ingestTimestamp" : "2026-06-13T10:35:05.241", "mongoId" : "69e1b5d82beec4dd3d1ac3fb", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/10382953/apply", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Analytical skills", "Problem-solving skills", "Time management skills", "Data annotation", "ML models", "Annotation processes", "Manage multiple simultaneous projects", "Reverse logistics processes", "ML domain" ], "skillCount" : 9, "jobCategory" : "operations", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "E-commerce" }, { "id" : "68c2e420f8b1b0376634c4b3", "title" : "Catalog Specialist, WWRR Science Annotation Team", "company" : "ADCI HYD", "industry" : "Fulfillment Operations Management, Catalog, Retail", "salary" : { "min" : 750000.0, "max" : 1250000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-seniority Catalog Specialist in Hyderabad, India, adjusted for the E-Commerce industry and company size." }, "location" : "Hyderabad, Telangana, IND", "locations" : [ "Hyderabad, Telangana, IND" ], "timestamp" : "2026-06-15T01:29:27.671", "fingerprint" : "01df7b504cb641afc4c01db94a9992e122c357cb8f887dea72a5f9302560dac2", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3078239/apply", "externalId" : "2c135fb0-8490-41b4-a4d3-63c6a1ad20b8", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Hyderabad", "state" : "Telangana", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "17.3605890,78.4740613" } ], "locationText" : "Hyderabad, Telangana, India", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 1, "experienceMaxYears" : 5, "experienceLevel" : "Mid", "technicalSkills" : "Machine Learning, ML models, Classification algorithms", "professionalSkills" : [ "Data annotation", "ML model training", "ML model evaluation" ], "hardSkillsList" : [ "Data annotation", "ML model training", "ML model evaluation", "Classification algorithms" ], "softSkillsList" : [ "Leadership", "Analytical skills", "Problem-solving skills" ], "hardSkills" : [ { "name" : "Data annotation", "level" : "intermediate" }, { "name" : "ML model training", "level" : "intermediate" }, { "name" : "ML model evaluation", "level" : "intermediate" }, { "name" : "Classification algorithms", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Analytical skills" }, { "name" : "Problem-solving skills" } ], "majorSkills" : "Data annotation, ML models, Classification algorithms", "majorSkillsList" : [ "Data annotation", "ML models", "Classification algorithms" ], "coreResponsibilities" : "Work closely with teams to support ML models, Perform data annotation to train and evaluate ML, Support data scientists in development of classification algorithms, Collaborate with cross-functional teams to ensure data annotation, Maintain high-quality standards for annotated data, Continuously evaluate and improve annotation processes, Deep-dive on complex problems, Manage multiple simultaneous projects", "teamCollaboration" : "Cross-functional teams; Product teams; Technology teams; Science teams", "projectManagementSkills" : [ "Time management" ], "domainKnowledge" : "Machine Learning; Classification algorithms; Reverse logistics", "domainList" : [ "machine-learning", "classification-algorithms", "reverse-logistics" ], "domainSpecificKnowledge" : [ "Machine Learning", "Classification algorithms", "Reverse logistics" ], "toolProficiency" : [ "Microsoft Office" ], "communicationSkills" : "Frequent communication", "innovationCreativity" : "Innovate", "problemSolvingSkills" : "Problem-solving skills", "outcomesObjectives" : "Delight customers through new experiences", "qualificationsBasic" : "Bachelor's degree, Speak, write, and read fluently in Italian, Experience with Microsoft Office products and applications, 1+ years of proven experience in data annotation and labeling for ML model training and evaluation, Minimum B2 Language Proficiency required", "qualificationsPreferred" : "Experience working on the MTurk platform for data annotation tasks, Proven experience in data annotation and labeling for ML model training and evaluation, Understanding of data annotation methodologies and tools, Familiarity with Amazon's product and category ecosystem, Previous exposure to machine learning concepts and algorithms, Demonstrated ability to adapt to evolving technologies and methodologies in the ML domain", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "In the Worldwide Returns, ReCommerce & Sustainability (WW RR&S) group at Amazon, we are dedicated to ‘making zero happen’ – zero cost of returns, zero waste, and zero defects – to benefit our customers, company, and environment. We are an agile and inclusive organization that constantly innovates to create long-term value by investing in our people and our planet, not simply focusing on the bottom line. WW R&R includes business, product, operations, data, and software engineering teams, who together manage the lifecycle of returned and damaged products. In WW R&R, you will partner across these teams to help customers discover great deals on quality used, rentals, and open box items; get the most value out of Amazon’s products; improve the customer returns experience; and reduce defects, waste, and cost in reverse logistics processes. You will be a leader, a builder, and an owner, collaborating cross-functionally with technical, operations, and business teams to design scalable and automated solutions to customer problems. Amazon is Earth’s most customer-centric company and in WW R&R, the Earth is our customer too. Come join us and innovate with the Amazon Worldwide Returns, ReCommerce & Sustainability team! We are hiring an experienced Catalog Specialist to help us grow our business in innovative ways. In this role, you will work closely with our product, technology and science teams to support new Machine Learning (ML) models and data science classification algorithm development – all helping to delight our customers through new experiences throughout their Amazon shopping journey. Need candidates in language proficiency in: German Key job responsibilities • Work closely with our product, technology, and science teams to support Machine Learning (ML) models • Perform data annotation required to train and evaluate ML models effectively • Support data scientists in the development of classification algorithms • Collaborate with cross-functional teams to ensure data annotation tasks align with project objectives and timelines • Maintain high-quality standards for annotated data to optimize model performance • Continuously evaluate and improve annotation processes to enhance efficiency and accuracy • Strong analytical skills and the ability to deep-dive on complex problems • Ability to manage multiple simultaneous projects requiring frequent communication, organization/time management and problem-solving skills Basic Qualifications: Bachelor's degree Speak, write, and read fluently in Italian Experience with Microsoft Office products and applications 1+ years of proven experience in data annotation and labeling for ML model training and evaluation Minimum B2 Language Proficiency required Preferred Qualifications: Experience working on the MTurk platform for data annotation tasks Proven experience in data annotation and labeling for ML model training and evaluation Understanding of data annotation methodologies and tools Familiarity with Amazon's product and category ecosystem Previous exposure to machine learning concepts and algorithms Demonstrated ability to adapt to evolving technologies and methodologies in the ML domain Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.", "summaryDescription" : "Catalog Specialist, WWRR Science Annotation Team at ADCI HYD. Skills: Data annotation, ML models, Classification algorithms. Work closely with teams to support ML models. Perform data annotation to train and evaluate ML", "postedDate" : "2026-06-13T06:34:52.207", "createdAt" : "2026-06-13T06:34:52.207", "lastUpdated" : "2026-06-15T01:29:27.671", "ingestTimestamp" : "2026-06-13T06:34:52.207", "mongoId" : "68c2e420f8b1b0376634c4b3", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3078239/apply", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Data annotation", "ML model training", "ML model evaluation", "Classification algorithms", "Leadership", "Analytical skills", "Problem-solving skills", "ML models", "Time management", "Machine Learning", "Reverse logistics", "Microsoft Office" ], "skillCount" : 12, "jobCategory" : "operations", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a2ca19574d8ee00a09a5ee0", "title" : "Data Annotation Team Leader", "industry" : "Data", "salary" : { "min" : 185000.0, "max" : 275000.0, "currency" : "AED", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for a Lead Data Annotation Team Leader in Dubai, United Arab Emirates, adjusted for the technology industry and full-time employment." }, "location" : "Dubai", "locations" : [ "Dubai" ], "timestamp" : "2026-06-16T00:45:16.946", "fingerprint" : "f4b3cbedc388016cbae863cb68f5be2f55cf21cb16d7534ec14bd5267ef3299c", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/weride/9d4fea10-e056-4ebe-8459-45cf00a9fcd0/apply", "externalId" : "9d4fea10-e056-4ebe-8459-45cf00a9fcd0", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Dubai", "country" : "United Arab Emirates", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "25.0742823,55.1885387" } ], "locationText" : "Dubai, United Arab Emirates", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 2, "experienceMaxYears" : 15, "experienceLevel" : "Lead", "technicalSkills" : "Data analysis", "professionalSkills" : [ "Root cause analysis", "Process enhancement", "Efficiency strategies" ], "hardSkillsList" : [ "Descriptive statistics", "Data cleaning", "Data preprocessing" ], "hardSkills" : [ { "name" : "Descriptive statistics", "level" : "intermediate" }, { "name" : "Data cleaning", "level" : "intermediate" }, { "name" : "Data preprocessing", "level" : "intermediate" } ], "majorSkills" : "Data annotation, Team leadership, Quality control", "majorSkillsList" : [ "Data annotation", "Team leadership", "Quality control" ], "coreResponsibilities" : "Lead training and development of overseas data annotators, Provide daily guidance and Q&A support, Document recurring challenges, Perform root-cause analysis, Implement effective solutions, Monitor feedback and acceptance outcomes, Refine annotation methodologies, Enhance annotation guidelines, Design quality control framework, Establish evaluation metrics, Conduct comprehensive audits, Prevent substandard data progression, Anticipate operational risks, Identify team management challenges, Recommend process enhancements, Recommend efficiency strategies, Own project timelines, Own quality benchmarks, Plan workloads strategically, Coordinate resources effectively, Deliver high-quality data on schedule", "teamCollaboration" : "Collaborate with stakeholders", "projectManagementSkills" : [ "Workload planning", "Resource coordination" ], "domainKnowledge" : "Data annotation guidelines", "domainList" : [ "data-annotation-guidelines" ], "domainSpecificKnowledge" : [ "Data annotation guidelines" ], "toolProficiency" : [ "Data analysis tools" ], "communicationSkills" : "Technical documentation", "documentationSkills" : "Annotation methodologies; Annotation guidelines", "problemSolvingSkills" : "Root cause analysis", "outcomesObjectives" : "Elevate team performance and consistency; Ensure quality standards are met; Exceed quality standards; Strengthen overall project execution; Surpass client expectations", "qualificationsBasic" : "Bachelor's degree or higher, Minimum 2.5 years experience in data annotation, English and Chinese proficiency (written and spoken), Able to read and interpret English annotation guidelines, Familiar with fundamental data analysis techniques, Proficient in using data analysis tools", "qualificationsPreferred" : "Experience in Data Annotation", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "## Key Responsibilities 1. Lead, Train & Empower Global Teams Drive the training and development of overseas data annotators, serving as the go-to expert for daily guidance and Q&A support. Proactively document recurring challenges, perform root-cause analysis, and implement effective solutions to elevate team performance and consistency. 2. Turn Feedback into Continuous Improvement Collaborate closely with stakeholders to monitor feedback and acceptance outcomes. Translate insights into actionable improvements by refining annotation methodologies and enhancing guidelines — ensuring quality standards are not only met but consistently exceeded. 3. Champion Quality Excellence Design and implement a robust quality control framework that oversees the entire annotation lifecycle. Establish clear evaluation metrics, conduct comprehensive audits, and safeguard project integrity by preventing substandard data from progressing downstream. 4. Optimize Processes & Drive Efficiency Anticipate operational risks and identify potential team management challenges before they arise. Leverage hands-on experience to recommend smart process enhancements and efficiency strategies that strengthen overall project execution. 5. Deliver with Precision & Accountability Own project timelines and quality benchmarks by strategically planning workloads and coordinating resources effectively. Ensure high-quality data is delivered on schedule, meeting — and surpassing — client expectations. ## Job Requirements 1. Education & Experience Bachelor’s degree or higher in a relevant field. Minimum 2.5 years experience in data annotation is required. Able to quickly understand project requirements and adapt to operational workflows. 2. Language Proficiency English and Chinese (written and spoken) is a MUST. Able to read and interpret English annotation guidelines and technical documentation accurately. Capable of supporting data annotation tasks for international projects. 3. Technical & Analytical Skills Familiar with fundamental data analysis techniques, including descriptive statistics, data cleaning, and preprocessing. Proficient in using data analysis tools to perform basic analysis on annotated datasets. Able to provide data-driven insights and recommendations to support annotation quality and decision-making. Experience in Data Annotation is preferable.", "summaryDescription" : "Data Annotation Team Leader. Skills: Data annotation, Team leadership, Quality control. Lead training and development of overseas data annotators. Provide daily guidance and Q&A support", "postedDate" : "2026-06-11T18:17:15.538", "createdAt" : "2026-06-11T18:17:15.538", "lastUpdated" : "2026-06-16T00:45:16.946", "ingestTimestamp" : "2026-06-14T21:45:57.813", "mongoId" : "6a2ca19574d8ee00a09a5ee0", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "150k-200k", "hasSalary" : false, "allSkills" : [ "Descriptive statistics", "Data cleaning", "Data preprocessing", "Data annotation", "Team leadership", "Quality control", "Root cause analysis", "Process enhancement", "Efficiency strategies", "Workload planning", "Resource coordination", "Data annotation guidelines", "Data analysis tools" ], "skillCount" : 13, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Lead", "dataQualityScore" : 0.8888889, "daysOld" : 4, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2ca60474d8ee00a09b90d2", "title" : "Junior English Language Specialist", "company" : "VSI", "industry" : "Media", "salary" : { "min" : 30000.0, "max" : 40000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Junior English Language Specialist in London, UK, with adjustments for entry-level experience and the media industry." }, "location" : "London, England, United Kingdom", "locations" : [ "London", "England", "United Kingdom" ], "timestamp" : "2026-06-15T08:27:46.222", "fingerprint" : "1cc506d8e079fe8f19ac32d6ac5120231054c80dce126d92d5404b3dcac7b44f", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/vsi/jobs/4882484101", "externalId" : "4882484101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "state" : "England", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "51.5074456,-0.1277653" }, { "country" : "United Kingdom", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "London, England, United Kingdom; United Kingdom", "employmentType" : "FULL_TIME", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "technicalSkills" : "Subtitling software, ASR engines, STT engines, MT engines", "professionalSkills" : [ "Linguistics", "Time management", "Organisational skills", "Technical aptitude" ], "hardSkillsList" : [ "English grammar", "Spelling conventions", "Subtitling", "Transcription", "Proofreading", "Translation", "Accessibility scripts", "Voice-over scripts", "Technical QC", "Terminology checks", "Style consistency", "Post-editing" ], "hardSkills" : [ { "name" : "English grammar", "level" : "intermediate" }, { "name" : "Spelling conventions", "level" : "intermediate" }, { "name" : "Subtitling", "level" : "intermediate" }, { "name" : "Transcription", "level" : "intermediate" }, { "name" : "Proofreading", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" }, { "name" : "Accessibility scripts", "level" : "intermediate" }, { "name" : "Voice-over scripts", "level" : "intermediate" }, { "name" : "Technical QC", "level" : "intermediate" }, { "name" : "Terminology checks", "level" : "intermediate" }, { "name" : "Style consistency", "level" : "intermediate" }, { "name" : "Post-editing", "level" : "intermediate" } ], "majorSkills" : "English proficiency, Subtitling, Proofreading, Technical QC", "majorSkillsList" : [ "English proficiency", "Subtitling", "Proofreading", "Technical QC" ], "coreResponsibilities" : "Maintain knowledge of English grammar, Produce English subtitles, Produce subtitle templates, Produce transcriptions, Produce translations, Produce accessibility scripts, Produce voice-over scripts, Proofread subtitles, Proofread captions, Proofread transcripts, Proofread internal documents, Perform technical QC, Correct timing, Correct positioning, Support evaluations of freelance suppliers, Provide in-house linguistic assistance, Support testing of new tools, Support implementation of new tools, Use subtitling software, Use internal tools, Create language guidelines, Update language guidelines, Create subtitling guidelines, Update subtitling guidelines, Advise on client-specific guidelines, Assist in testing ASR engines, Assist in testing STT engines, Assist in testing MT engines, Assess engine accuracy", "teamCollaboration" : "QC department; Freelance suppliers", "domainKnowledge" : "Media localisation; Subtitling specifications; Audiovisual translation", "domainList" : [ "media-localisation", "subtitling-specifications", "audiovisual-translation" ], "domainSpecificKnowledge" : [ "Media localisation", "Subtitling specifications", "Audiovisual translation" ], "toolProficiency" : [ "EZTitles", "OOONA" ], "communicationSkills" : "Communication skills", "documentationSkills" : "Style guide expertise; Language guidelines; Subtitling guidelines", "continuousLearning" : "Expanding expertise in localisation", "problemSolvingSkills" : "Attention to detail; Accuracy", "qualificationsBasic" : "Native-level command of English, Internship, freelance, or academic experience in subtitling, transcription, or proofreading, Familiarity with different subtitling specifications and software, Technical aptitude, Ability to quickly learn new tools, Excellent organisational and time management skills, Ability to work independently, Self-motivation and initiative", "qualificationsPreferred" : "Degree in audiovisual translation, Copywriting/creative writing experience, Knowledge of MT/ASR/STT post-editing, MT/ASR/STT engine testing experience, Ability to speak another language, 6–12 months+ experience in subtitling, transcription, or proofreading", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Want to join a global company that brings the world together by producing premium media content in over 80 languages worldwide? VSI provides language localisation and media services to the biggest brands in streaming and media entertainment. Headquartered in London, VSI consists of a global network of state-of-the-art studio facilities that use the world's best voice acting talent to tell the stories of our most watched movies and television series. VSI works across a wide range of media sectors from streaming platforms, traditional broadcast television, theatrical releases and gaming. Job Overview VSI’s Subtitling Technology and QC department is responsible for providing subtitling technical and style guide expertise to the business, upholding the company’s high linguistic and technical standards whilst carrying out QC, subtitling, proofreading, test evaluations and subtitling tool training amongst other tasks. We are looking for a proactive individual to join us as Junior English Language Specialist in our department on a permanent basis. You will need to have a solid background in linguistics, be technically minded, have excellent time management, and organisational and communication skills. This is an exciting opportunity to work hands-on with leading subtitling tools and workflows, while building valuable experience and expanding your expertise in localisation. Fully remote applications considered. Key responsibilities Maintain an up-to-date knowledge of English grammar and spelling conventions Produce English subtitles/closed captions, subtitle templates, transcriptions, translations, accessibility scripts, and voice-over scripts for corporate videos, broadcast material, and VOD platforms for a variety of high-profile clients Proofread subtitles, captions, transcripts, and internal documents Perform technical QC on English subtitle templates, correcting timing, positioning, and other technical elements Support evaluations of freelance suppliers Provide in-house linguistic assistance (e.g., terminology checks, style consistency) Support the testing and implementation of new tools Use subtitling software (e.g., EZTitles, OOONA) and internal tools Assist in creating and updating language and subtitling guidelines for internal and external use Advise on client-specific subtitling and language guidelines as required Assist in testing ASR/STT and MT engines, assessing their accuracy based on content type and language Essential skills and experience In order to be successful for this role, candidates must demonstrate the following: English proficiency: Native-level command of English with excellent grammar, spelling, and style Internship, freelance, or academic experience in subtitling, transcription, or proofreading (6–12 months+ is a plus) Familiarity with different subtitling specifications and software, ideally EZTitles and OOONA Technical aptitude and the ability to quickly learn new tools Excellent organisational and time management skills Ability to work independently in a fast-paced work environment Strong attention to detail and accuracy Self-motivation and initiative Desirable skills Degree in audiovisual translation or similar Copywriting/creative writing experience Knowledge of MT/ASR/STT post-editing MT/ASR/STT engine testing experience Ability to speak another language What else is on offer? Private medical insurance Enrolment to company salary sacrifice pension scheme Discounted gym membership Cycle-to-work scheme Travel card loan Regular social activities", "summaryDescription" : "Junior English Language Specialist at VSI. Skills: English proficiency, Subtitling, Proofreading, Technical QC. Maintain knowledge of English grammar. Produce English subtitles", "postedDate" : "2026-06-14T01:59:32.238", "createdAt" : "2026-06-14T01:59:32.238", "lastUpdated" : "2026-06-15T08:27:46.222", "ingestTimestamp" : "2026-06-14T01:59:32.238", "mongoId" : "6a2ca60474d8ee00a09b90d2", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "30k-50k", "hasSalary" : false, "allSkills" : [ "English grammar", "Spelling conventions", "Subtitling", "Transcription", "Proofreading", "Translation", "Accessibility scripts", "Voice-over scripts", "Technical QC", "Terminology checks", "Style consistency", "Post-editing", "English proficiency", "Linguistics", "Time management", "Organisational skills", "Technical aptitude", "Media localisation", "Subtitling specifications", "Audiovisual translation", "EZTitles", "OOONA" ], "skillCount" : 22, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Junior", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Media", "llmIndustryConfidence" : 0.92 }, { "id" : "6a306073f292fd229cf8dc78", "title" : "Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project", "company" : "Meridial", "salary" : { "min" : 6.0, "max" : 20.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Worldwide - Remote", "locations" : [ "Worldwide - Remote" ], "timestamp" : "2026-06-16T07:22:37.846", "fingerprint" : "cee893319153a3a26f45d7279ddd48fb28d5a4d98d25442ad9c902aafbdd2fbc", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/agency/jobs/4781824101", "externalId" : "4781824101", "industryFunction" : { }, "structuredLocations" : [ { "workMode" : "remote" } ], "locationText" : "", "employmentType" : "CONTRACT", "hardSkillsList" : [ "Pavement condition assessment", "Pavement distress identification" ], "hardSkills" : [ { "name" : "Pavement condition assessment", "level" : "intermediate" }, { "name" : "Pavement distress identification", "level" : "intermediate" } ], "majorSkills" : "PCI surveys, Pavement condition, Annotation tasks", "majorSkillsList" : [ "PCI surveys", "Pavement condition", "Annotation tasks" ], "coreResponsibilities" : "Review roadway images, Review inspection records, Review AI-generated outputs, Determine accuracy of distress types, Determine accuracy of severity levels, Determine accuracy of condition assessments, Annotate pavement features, Validate pavement features, Annotate distress patterns, Validate distress patterns, Analyze roadway imagery, Analyze survey excerpts, Validate AI-generated classifications, Provide written feedback, Clarify inspector distinctions, Clarify sampling unit evaluation, Clarify field condition influence", "domainKnowledge" : "Pavement Condition Index (PCI); Pavement distress types; Pavement severity levels; Pavement condition ratings; Roadway conditions; Infrastructure maintenance planning; Cracking; Rutting; Spalling; Patching; Weathering", "domainList" : [ "pavement-condition-index-pci", "pavement-distress-types", "pavement-severity-levels", "pavement-condition-ratings", "roadway-conditions", "infrastructure-maintenance-planning", "cracking", "rutting", "spalling", "patching", "weathering" ], "domainSpecificKnowledge" : [ "Pavement Condition Index (PCI)", "Pavement distress types", "Pavement severity levels", "Pavement condition ratings", "Roadway conditions", "Infrastructure maintenance planning", "Cracking", "Rutting", "Spalling", "Patching", "Weathering" ], "communicationSkills" : "Written feedback; Explain inspection reasoning; Explain classification decisions", "qualificationsBasic" : "Familiarity with PCI surveys, Attention to visual detail, Ability to apply distress definitions, Ability to apply rating criteria", "qualificationsPreferred" : "Experience with inspection imagery, Experience with condition reports, Experience with roadway maintenance planning", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Are you a pavement professional or roadway inspector with hands-on experience conducting or interpreting Pavement Condition Index (PCI) surveys? Advanced AI systems are being developed to understand roadway conditions, interpret inspection imagery, and support infrastructure maintenance planning. High-quality training data based on real PCI survey practices is essential to ensure these systems accurately recognize pavement distress and condition ratings. This project relies on your expertise to help train and evaluate next-generation AI models. In this project, you will focus specifically on PCI-related workflows and annotation tasks. You will review roadway images, inspection records, and AI-generated outputs to determine whether pavement distress types, severity levels, and condition assessments are accurate and consistent with PCI methodology. A central part of the work involves annotating or validating pavement features and distress patterns so models can better learn to identify cracking, rutting, spalling, patching, weathering, and other common pavement conditions. On a typical day, you may analyze roadway imagery or survey excerpts, validate AI-generated classifications of pavement distress, and provide written feedback explaining where models misidentify features or misinterpret severity levels. You may also help clarify how inspectors distinguish between similar distress categories, how sampling units are evaluated, and how real-world field conditions influence PCI scoring and reporting. This project is well suited for pavement engineers, civil or transportation engineers, DOT specialists, highway inspectors, and other professionals who have conducted or reviewed PCI surveys or pavement condition assessments. Experience working with inspection imagery, condition reports, or roadway maintenance planning is highly valuable. Clear written communication and the ability to explain inspection reasoning and classification decisions in a structured way are essential. No prior AI or technical background is required. Training and project guidelines will be provided. What matters most is your familiarity with PCI surveys, attention to visual detail, and ability to consistently apply pavement distress definitions and rating criteria. We offer a pay range of $6 - $20 per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above. As a contractor, you will supply a secure computer and high-speed internet; company-sponsored benefits such as health insurance and PTO do not apply. Job title: Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project Employment type: Freelance / Contract Workplace type: Remote", "summaryDescription" : "Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project at Meridial. Skills: PCI surveys, Pavement condition, Annotation tasks. Review roadway images. Review inspection records", "postedDate" : "2026-06-15T23:29:29.926", "createdAt" : "2026-06-15T23:29:29.926", "lastUpdated" : "2026-06-16T07:22:37.846", "ingestTimestamp" : "2026-06-15T23:29:29.926", "mongoId" : "6a306073f292fd229cf8dc78", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 12480, "salaryAnnualMax" : 41600, "salaryBand" : "<30k", "hasSalary" : true, "allSkills" : [ "Pavement condition assessment", "Pavement distress identification", "PCI surveys", "Pavement condition", "Annotation tasks", "Pavement Condition Index (PCI)", "Pavement distress types", "Pavement severity levels", "Pavement condition ratings", "Roadway conditions", "Infrastructure maintenance planning", "Cracking", "Rutting", "Spalling", "Patching", "Weathering" ], "skillCount" : 16, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.92 }, { "id" : "6a306073f292fd229cf8dc77", "title" : "Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project", "company" : "Meridial", "salary" : { "min" : 6.0, "max" : 20.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Worldwide - Remote", "locations" : [ "Worldwide - Remote" ], "timestamp" : "2026-06-16T07:24:40.323", "fingerprint" : "d8b2f9b58bd8a069f5192092c4349eccb8a5307ec082aea6e61391486e695cc6", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/agency/jobs/4781816101", "externalId" : "4781816101", "industryFunction" : { }, "structuredLocations" : [ { "workMode" : "remote" } ], "locationText" : "", "employmentType" : "CONTRACT", "hardSkillsList" : [ "PCI surveys", "Pavement distress identification", "Condition assessment" ], "hardSkills" : [ { "name" : "PCI surveys", "level" : "intermediate" }, { "name" : "Pavement distress identification", "level" : "intermediate" }, { "name" : "Condition assessment", "level" : "intermediate" } ], "majorSkills" : "PCI surveys, Pavement condition assessment, AI model training", "majorSkillsList" : [ "PCI surveys", "Pavement condition assessment", "AI model training" ], "coreResponsibilities" : "Review roadway images, Review inspection records, Review AI-generated outputs, Determine accuracy of distress types, Determine accuracy of severity levels, Determine accuracy of condition assessments, Annotate pavement features, Validate pavement features, Annotate distress patterns, Validate distress patterns, Analyze roadway imagery, Analyze survey excerpts, Validate AI-generated classifications, Provide written feedback, Clarify inspector distinctions, Clarify sampling unit evaluation, Clarify field condition influence", "domainKnowledge" : "Pavement Condition Index (PCI); Pavement distress types; Pavement severity levels; Pavement condition ratings; Roadway inspection; Infrastructure maintenance planning", "domainList" : [ "pavement-condition-index-pci", "pavement-distress-types", "pavement-severity-levels", "pavement-condition-ratings", "roadway-inspection", "infrastructure-maintenance-planning" ], "domainSpecificKnowledge" : [ "Pavement Condition Index (PCI)", "Pavement distress types", "Pavement severity levels", "Pavement condition ratings", "Roadway inspection", "Infrastructure maintenance planning" ], "communicationSkills" : "Written feedback; Explain inspection reasoning; Explain classification decisions", "qualificationsBasic" : "Familiarity with PCI surveys, Attention to visual detail, Ability to apply distress definitions, Ability to apply rating criteria", "qualificationsPreferred" : "Experience with inspection imagery, Experience with condition reports, Experience with roadway maintenance planning", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Are you a pavement professional or roadway inspector with hands-on experience conducting or interpreting Pavement Condition Index (PCI) surveys? Advanced AI systems are being developed to understand roadway conditions, interpret inspection imagery, and support infrastructure maintenance planning. High-quality training data based on real PCI survey practices is essential to ensure these systems accurately recognize pavement distress and condition ratings. This project relies on your expertise to help train and evaluate next-generation AI models. In this project, you will focus specifically on PCI-related workflows and annotation tasks. You will review roadway images, inspection records, and AI-generated outputs to determine whether pavement distress types, severity levels, and condition assessments are accurate and consistent with PCI methodology. A central part of the work involves annotating or validating pavement features and distress patterns so models can better learn to identify cracking, rutting, spalling, patching, weathering, and other common pavement conditions. On a typical day, you may analyze roadway imagery or survey excerpts, validate AI-generated classifications of pavement distress, and provide written feedback explaining where models misidentify features or misinterpret severity levels. You may also help clarify how inspectors distinguish between similar distress categories, how sampling units are evaluated, and how real-world field conditions influence PCI scoring and reporting. This project is well suited for pavement engineers, civil or transportation engineers, DOT specialists, highway inspectors, and other professionals who have conducted or reviewed PCI surveys or pavement condition assessments. Experience working with inspection imagery, condition reports, or roadway maintenance planning is highly valuable. Clear written communication and the ability to explain inspection reasoning and classification decisions in a structured way are essential. No prior AI or technical background is required. Training and project guidelines will be provided. What matters most is your familiarity with PCI surveys, attention to visual detail, and ability to consistently apply pavement distress definitions and rating criteria. We offer a pay range of $6 - $20 per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above. As a contractor, you will supply a secure computer and high-speed internet; company-sponsored benefits such as health insurance and PTO do not apply. Job title: Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project Employment type: Freelance / Contract Workplace type: Remote", "summaryDescription" : "Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project at Meridial. Skills: PCI surveys, Pavement condition assessment, AI model training. Review roadway images. Review inspection records", "postedDate" : "2026-06-15T23:28:37.251", "createdAt" : "2026-06-15T23:28:37.251", "lastUpdated" : "2026-06-16T07:24:40.323", "ingestTimestamp" : "2026-06-15T23:28:37.251", "mongoId" : "6a306073f292fd229cf8dc77", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 12480, "salaryAnnualMax" : 41600, "salaryBand" : "<30k", "hasSalary" : true, "allSkills" : [ "PCI surveys", "Pavement distress identification", "Condition assessment", "Pavement condition assessment", "AI model training", "Pavement Condition Index (PCI)", "Pavement distress types", "Pavement severity levels", "Pavement condition ratings", "Roadway inspection", "Infrastructure maintenance planning" ], "skillCount" : 11, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.92 }, { "id" : "6a306073f292fd229cf8dc76", "title" : "Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project", "company" : "Meridial", "salary" : { "min" : 6.0, "max" : 20.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Worldwide - Remote", "locations" : [ "Worldwide - Remote" ], "timestamp" : "2026-06-16T08:57:41.637", "fingerprint" : "bbcfc9cafcb5de707855b6640efd50e95737f9c9a74c303e603eae603595f87d", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/agency/jobs/4781817101", "externalId" : "4781817101", "industryFunction" : { }, "structuredLocations" : [ { "workMode" : "remote" } ], "locationText" : "", "employmentType" : "CONTRACT", "hardSkillsList" : [ "PCI surveys", "Pavement distress identification", "Condition assessment" ], "hardSkills" : [ { "name" : "PCI surveys", "level" : "intermediate" }, { "name" : "Pavement distress identification", "level" : "intermediate" }, { "name" : "Condition assessment", "level" : "intermediate" } ], "majorSkills" : "PCI surveys, Pavement condition assessment, AI model training", "majorSkillsList" : [ "PCI surveys", "Pavement condition assessment", "AI model training" ], "coreResponsibilities" : "Review roadway images, Review inspection records, Review AI-generated outputs, Determine accuracy of distress types, Determine accuracy of severity levels, Determine accuracy of condition assessments, Annotate pavement features, Validate pavement features, Annotate distress patterns, Validate distress patterns, Analyze roadway imagery, Analyze survey excerpts, Validate AI-generated classifications, Provide written feedback, Clarify inspector distinctions, Clarify sampling unit evaluation, Clarify real-world condition influence", "domainKnowledge" : "Pavement Condition Index (PCI); Pavement distress types; Pavement severity levels; Pavement condition ratings; Roadway inspection; Infrastructure maintenance planning", "domainList" : [ "pavement-condition-index-pci", "pavement-distress-types", "pavement-severity-levels", "pavement-condition-ratings", "roadway-inspection", "infrastructure-maintenance-planning" ], "domainSpecificKnowledge" : [ "Pavement Condition Index (PCI)", "Pavement distress types", "Pavement severity levels", "Pavement condition ratings", "Roadway inspection", "Infrastructure maintenance planning" ], "communicationSkills" : "Written feedback; Explain inspection reasoning; Explain classification decisions", "qualificationsBasic" : "Familiarity with PCI surveys, Attention to visual detail, Ability to apply distress definitions, Ability to apply rating criteria", "qualificationsPreferred" : "Experience with inspection imagery, Experience with condition reports, Experience with roadway maintenance planning", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Are you a pavement professional or roadway inspector with hands-on experience conducting or interpreting Pavement Condition Index (PCI) surveys? Advanced AI systems are being developed to understand roadway conditions, interpret inspection imagery, and support infrastructure maintenance planning. High-quality training data based on real PCI survey practices is essential to ensure these systems accurately recognize pavement distress and condition ratings. This project relies on your expertise to help train and evaluate next-generation AI models. In this project, you will focus specifically on PCI-related workflows and annotation tasks. You will review roadway images, inspection records, and AI-generated outputs to determine whether pavement distress types, severity levels, and condition assessments are accurate and consistent with PCI methodology. A central part of the work involves annotating or validating pavement features and distress patterns so models can better learn to identify cracking, rutting, spalling, patching, weathering, and other common pavement conditions. On a typical day, you may analyze roadway imagery or survey excerpts, validate AI-generated classifications of pavement distress, and provide written feedback explaining where models misidentify features or misinterpret severity levels. You may also help clarify how inspectors distinguish between similar distress categories, how sampling units are evaluated, and how real-world field conditions influence PCI scoring and reporting. This project is well suited for pavement engineers, civil or transportation engineers, DOT specialists, highway inspectors, and other professionals who have conducted or reviewed PCI surveys or pavement condition assessments. Experience working with inspection imagery, condition reports, or roadway maintenance planning is highly valuable. Clear written communication and the ability to explain inspection reasoning and classification decisions in a structured way are essential. No prior AI or technical background is required. Training and project guidelines will be provided. What matters most is your familiarity with PCI surveys, attention to visual detail, and ability to consistently apply pavement distress definitions and rating criteria. We offer a pay range of $6 - $20 per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above. As a contractor, you will supply a secure computer and high-speed internet; company-sponsored benefits such as health insurance and PTO do not apply. Job title: Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project Employment type: Freelance / Contract Workplace type: Remote", "summaryDescription" : "Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project at Meridial. Skills: PCI surveys, Pavement condition assessment, AI model training. Review roadway images. Review inspection records", "postedDate" : "2026-06-15T23:27:14.421", "createdAt" : "2026-06-15T23:27:14.421", "lastUpdated" : "2026-06-16T08:57:41.637", "ingestTimestamp" : "2026-06-15T23:27:14.421", "mongoId" : "6a306073f292fd229cf8dc76", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 12480, "salaryAnnualMax" : 41600, "salaryBand" : "<30k", "hasSalary" : true, "allSkills" : [ "PCI surveys", "Pavement distress identification", "Condition assessment", "Pavement condition assessment", "AI model training", "Pavement Condition Index (PCI)", "Pavement distress types", "Pavement severity levels", "Pavement condition ratings", "Roadway inspection", "Infrastructure maintenance planning" ], "skillCount" : 11, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.92 }, { "id" : "6a306073f292fd229cf8dc7a", "title" : "Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project", "company" : "Meridial", "salary" : { "min" : 6.0, "max" : 20.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Worldwide - Remote", "locations" : [ "Worldwide - Remote" ], "timestamp" : "2026-06-16T10:21:28.891", "fingerprint" : "e482d56ee0826e185b0d76ea2bb24c65dda4f2144662f7c206ab9e166c67cb13", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/agency/jobs/4781822101", "externalId" : "4781822101", "industryFunction" : { }, "structuredLocations" : [ { "workMode" : "remote" } ], "locationText" : "", "employmentType" : "CONTRACT", "hardSkillsList" : [ "Pavement condition assessment", "Pavement distress identification", "Roadway inspection" ], "hardSkills" : [ { "name" : "Pavement condition assessment", "level" : "intermediate" }, { "name" : "Pavement distress identification", "level" : "intermediate" }, { "name" : "Roadway inspection", "level" : "intermediate" } ], "majorSkills" : "PCI surveys, Pavement condition, Annotation tasks", "majorSkillsList" : [ "PCI surveys", "Pavement condition", "Annotation tasks" ], "coreResponsibilities" : "Review roadway images, Review inspection records, Review AI-generated outputs, Determine accuracy of distress types, Determine accuracy of severity levels, Determine accuracy of condition assessments, Annotate pavement features, Validate pavement features, Annotate pavement distress patterns, Validate pavement distress patterns, Analyze roadway imagery, Analyze survey excerpts, Validate AI-generated classifications, Provide written feedback, Clarify inspector distinctions, Clarify sampling unit evaluation, Clarify field condition influence on scoring, Clarify field condition influence on reporting", "domainKnowledge" : "Pavement Condition Index (PCI); Pavement distress types; Pavement severity levels; Pavement condition ratings; Cracking; Rutting; Spalling; Patching; Weathering", "domainList" : [ "pavement-condition-index-pci", "pavement-distress-types", "pavement-severity-levels", "pavement-condition-ratings", "cracking", "rutting", "spalling", "patching", "weathering" ], "domainSpecificKnowledge" : [ "Pavement Condition Index (PCI)", "Pavement distress types", "Pavement severity levels", "Pavement condition ratings", "Cracking", "Rutting", "Spalling", "Patching", "Weathering" ], "communicationSkills" : "Written feedback; Explain reasoning", "qualificationsBasic" : "Familiarity with PCI surveys, Attention to visual detail, Ability to apply distress definitions, Ability to apply rating criteria, Clear written communication", "qualificationsPreferred" : "Experience with inspection imagery, Experience with condition reports, Experience with roadway maintenance planning", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Are you a pavement professional or roadway inspector with hands-on experience conducting or interpreting Pavement Condition Index (PCI) surveys? Advanced AI systems are being developed to understand roadway conditions, interpret inspection imagery, and support infrastructure maintenance planning. High-quality training data based on real PCI survey practices is essential to ensure these systems accurately recognize pavement distress and condition ratings. This project relies on your expertise to help train and evaluate next-generation AI models. In this project, you will focus specifically on PCI-related workflows and annotation tasks. You will review roadway images, inspection records, and AI-generated outputs to determine whether pavement distress types, severity levels, and condition assessments are accurate and consistent with PCI methodology. A central part of the work involves annotating or validating pavement features and distress patterns so models can better learn to identify cracking, rutting, spalling, patching, weathering, and other common pavement conditions. On a typical day, you may analyze roadway imagery or survey excerpts, validate AI-generated classifications of pavement distress, and provide written feedback explaining where models misidentify features or misinterpret severity levels. You may also help clarify how inspectors distinguish between similar distress categories, how sampling units are evaluated, and how real-world field conditions influence PCI scoring and reporting. This project is well suited for pavement engineers, civil or transportation engineers, DOT specialists, highway inspectors, and other professionals who have conducted or reviewed PCI surveys or pavement condition assessments. Experience working with inspection imagery, condition reports, or roadway maintenance planning is highly valuable. Clear written communication and the ability to explain inspection reasoning and classification decisions in a structured way are essential. No prior AI or technical background is required. Training and project guidelines will be provided. What matters most is your familiarity with PCI surveys, attention to visual detail, and ability to consistently apply pavement distress definitions and rating criteria. We offer a pay range of $6 - $20 per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above. As a contractor, you will supply a secure computer and high-speed internet; company-sponsored benefits such as health insurance and PTO do not apply. Job title: Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project Employment type: Freelance / Contract Workplace type: Remote", "summaryDescription" : "Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project at Meridial. Skills: PCI surveys, Pavement condition, Annotation tasks. Review roadway images. Review inspection records", "postedDate" : "2026-06-15T23:26:26.766", "createdAt" : "2026-06-15T23:26:26.766", "lastUpdated" : "2026-06-16T10:21:28.891", "ingestTimestamp" : "2026-06-15T23:26:26.766", "mongoId" : "6a306073f292fd229cf8dc7a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 12480, "salaryAnnualMax" : 41600, "salaryBand" : "<30k", "hasSalary" : true, "allSkills" : [ "Pavement condition assessment", "Pavement distress identification", "Roadway inspection", "PCI surveys", "Pavement condition", "Annotation tasks", "Pavement Condition Index (PCI)", "Pavement distress types", "Pavement severity levels", "Pavement condition ratings", "Cracking", "Rutting", "Spalling", "Patching", "Weathering" ], "skillCount" : 15, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.92 }, { "id" : "6a306073f292fd229cf8dc7d", "title" : "Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project", "company" : "Meridial", "salary" : { "min" : 6.0, "max" : 20.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Worldwide - Remote", "locations" : [ "Worldwide - Remote" ], "timestamp" : "2026-06-16T08:06:09.373", "fingerprint" : "98c6b011042b0f27ba3c7a2b62710e2b07e83f1afa741da1c880e3229a2917cd", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/agency/jobs/4775898101", "externalId" : "4775898101", "industryFunction" : { }, "structuredLocations" : [ { "workMode" : "remote" } ], "locationText" : "", "employmentType" : "CONTRACT", "hardSkillsList" : [ "Pavement condition assessment", "Pavement distress identification" ], "hardSkills" : [ { "name" : "Pavement condition assessment", "level" : "intermediate" }, { "name" : "Pavement distress identification", "level" : "intermediate" } ], "majorSkills" : "PCI surveys, Pavement condition, Annotation tasks", "majorSkillsList" : [ "PCI surveys", "Pavement condition", "Annotation tasks" ], "coreResponsibilities" : "Review roadway images, Review inspection records, Review AI-generated outputs, Determine accuracy of distress types, Determine accuracy of severity levels, Determine accuracy of condition assessments, Annotate pavement features, Validate pavement features, Annotate distress patterns, Validate distress patterns, Analyze roadway imagery, Analyze survey excerpts, Validate AI-generated classifications, Provide written feedback, Clarify inspector distinctions, Clarify sampling unit evaluation, Clarify field condition influence", "domainKnowledge" : "Pavement Condition Index (PCI); Pavement distress types; Pavement severity levels; Pavement condition ratings; Roadway conditions; Infrastructure maintenance planning; Pavement distress definitions; Rating criteria", "domainList" : [ "pavement-condition-index-pci", "pavement-distress-types", "pavement-severity-levels", "pavement-condition-ratings", "roadway-conditions", "infrastructure-maintenance-planning", "pavement-distress-definitions", "rating-criteria" ], "domainSpecificKnowledge" : [ "Pavement Condition Index (PCI)", "Pavement distress types", "Pavement severity levels", "Pavement condition ratings", "Roadway conditions", "Infrastructure maintenance planning", "Pavement distress definitions", "Rating criteria" ], "communicationSkills" : "Written feedback; Explain inspection reasoning; Explain classification decisions", "qualificationsBasic" : "Familiarity with PCI surveys, Attention to visual detail, Ability to apply distress definitions, Ability to apply rating criteria", "qualificationsPreferred" : "Experience with inspection imagery, Experience with condition reports, Experience with roadway maintenance planning", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Are you a pavement professional or roadway inspector with hands-on experience conducting or interpreting Pavement Condition Index (PCI) surveys? Advanced AI systems are being developed to understand roadway conditions, interpret inspection imagery, and support infrastructure maintenance planning. High-quality training data based on real PCI survey practices is essential to ensure these systems accurately recognize pavement distress and condition ratings. This project relies on your expertise to help train and evaluate next-generation AI models. In this project, you will focus specifically on PCI-related workflows and annotation tasks. You will review roadway images, inspection records, and AI-generated outputs to determine whether pavement distress types, severity levels, and condition assessments are accurate and consistent with PCI methodology. A central part of the work involves annotating or validating pavement features and distress patterns so models can better learn to identify cracking, rutting, spalling, patching, weathering, and other common pavement conditions. On a typical day, you may analyze roadway imagery or survey excerpts, validate AI-generated classifications of pavement distress, and provide written feedback explaining where models misidentify features or misinterpret severity levels. You may also help clarify how inspectors distinguish between similar distress categories, how sampling units are evaluated, and how real-world field conditions influence PCI scoring and reporting. This project is well suited for pavement engineers, civil or transportation engineers, DOT specialists, highway inspectors, and other professionals who have conducted or reviewed PCI surveys or pavement condition assessments. Experience working with inspection imagery, condition reports, or roadway maintenance planning is highly valuable. Clear written communication and the ability to explain inspection reasoning and classification decisions in a structured way are essential. No prior AI or technical background is required. Training and project guidelines will be provided. What matters most is your familiarity with PCI surveys, attention to visual detail, and ability to consistently apply pavement distress definitions and rating criteria. We offer a pay range of $6 - $20 per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above. As a contractor, you will supply a secure computer and high-speed internet; company-sponsored benefits such as health insurance and PTO do not apply. Job title: Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project Employment type: Freelance / Contract Workplace type: Remote", "summaryDescription" : "Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project at Meridial. Skills: PCI surveys, Pavement condition, Annotation tasks. Review roadway images. Review inspection records", "postedDate" : "2026-06-15T23:26:14.424", "createdAt" : "2026-06-15T23:26:14.424", "lastUpdated" : "2026-06-16T08:06:09.373", "ingestTimestamp" : "2026-06-15T23:26:14.424", "mongoId" : "6a306073f292fd229cf8dc7d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 12480, "salaryAnnualMax" : 41600, "salaryBand" : "<30k", "hasSalary" : true, "allSkills" : [ "Pavement condition assessment", "Pavement distress identification", "PCI surveys", "Pavement condition", "Annotation tasks", "Pavement Condition Index (PCI)", "Pavement distress types", "Pavement severity levels", "Pavement condition ratings", "Roadway conditions", "Infrastructure maintenance planning", "Pavement distress definitions", "Rating criteria" ], "skillCount" : 13, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.92 }, { "id" : "6a306073f292fd229cf8dc7c", "title" : "Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project", "company" : "Meridial", "salary" : { "min" : 6.0, "max" : 20.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Worldwide - Remote", "locations" : [ "Worldwide - Remote" ], "timestamp" : "2026-06-16T07:35:33.194", "fingerprint" : "81c01d0754615f03b79e3fba0704e37c572c4439b7d4df2c90a12fbf27058e12", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/agency/jobs/4781818101", "externalId" : "4781818101", "industryFunction" : { }, "structuredLocations" : [ { "workMode" : "remote" } ], "locationText" : "", "employmentType" : "CONTRACT", "hardSkillsList" : [ "Pavement condition assessment", "Pavement distress identification", "Pavement rating criteria" ], "hardSkills" : [ { "name" : "Pavement condition assessment", "level" : "intermediate" }, { "name" : "Pavement distress identification", "level" : "intermediate" }, { "name" : "Pavement rating criteria", "level" : "intermediate" } ], "majorSkills" : "PCI surveys, Pavement distress, Condition assessment", "majorSkillsList" : [ "PCI surveys", "Pavement distress", "Condition assessment" ], "coreResponsibilities" : "Review roadway images, Review inspection records, Review AI-generated outputs, Determine accuracy of distress types, Determine accuracy of severity levels, Determine accuracy of condition assessments, Annotate pavement features, Validate pavement features, Annotate distress patterns, Validate distress patterns, Analyze roadway imagery, Analyze survey excerpts, Validate AI-generated classifications, Provide written feedback, Clarify inspector distinctions, Clarify sampling unit evaluation, Clarify field condition influence", "domainKnowledge" : "Pavement Condition Index (PCI); Pavement distress types; Pavement severity levels; Pavement condition ratings; Roadway imagery analysis; Infrastructure maintenance planning", "domainList" : [ "pavement-condition-index-pci", "pavement-distress-types", "pavement-severity-levels", "pavement-condition-ratings", "roadway-imagery-analysis", "infrastructure-maintenance-planning" ], "domainSpecificKnowledge" : [ "Pavement Condition Index (PCI)", "Pavement distress types", "Pavement severity levels", "Pavement condition ratings", "Roadway imagery analysis", "Infrastructure maintenance planning" ], "communicationSkills" : "Written feedback; Explain inspection reasoning; Explain classification decisions", "qualificationsBasic" : "Familiarity with PCI surveys, Attention to visual detail, Ability to apply distress definitions, Ability to apply rating criteria", "qualificationsPreferred" : "Experience with inspection imagery, Experience with condition reports, Experience with roadway maintenance planning", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Are you a pavement professional or roadway inspector with hands-on experience conducting or interpreting Pavement Condition Index (PCI) surveys? Advanced AI systems are being developed to understand roadway conditions, interpret inspection imagery, and support infrastructure maintenance planning. High-quality training data based on real PCI survey practices is essential to ensure these systems accurately recognize pavement distress and condition ratings. This project relies on your expertise to help train and evaluate next-generation AI models. In this project, you will focus specifically on PCI-related workflows and annotation tasks. You will review roadway images, inspection records, and AI-generated outputs to determine whether pavement distress types, severity levels, and condition assessments are accurate and consistent with PCI methodology. A central part of the work involves annotating or validating pavement features and distress patterns so models can better learn to identify cracking, rutting, spalling, patching, weathering, and other common pavement conditions. On a typical day, you may analyze roadway imagery or survey excerpts, validate AI-generated classifications of pavement distress, and provide written feedback explaining where models misidentify features or misinterpret severity levels. You may also help clarify how inspectors distinguish between similar distress categories, how sampling units are evaluated, and how real-world field conditions influence PCI scoring and reporting. This project is well suited for pavement engineers, civil or transportation engineers, DOT specialists, highway inspectors, and other professionals who have conducted or reviewed PCI surveys or pavement condition assessments. Experience working with inspection imagery, condition reports, or roadway maintenance planning is highly valuable. Clear written communication and the ability to explain inspection reasoning and classification decisions in a structured way are essential. No prior AI or technical background is required. Training and project guidelines will be provided. What matters most is your familiarity with PCI surveys, attention to visual detail, and ability to consistently apply pavement distress definitions and rating criteria. We offer a pay range of $6 - $20 per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above. As a contractor, you will supply a secure computer and high-speed internet; company-sponsored benefits such as health insurance and PTO do not apply. Job title: Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project Employment type: Freelance / Contract Workplace type: Remote", "summaryDescription" : "Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project at Meridial. Skills: PCI surveys, Pavement distress, Condition assessment. Review roadway images. Review inspection records", "postedDate" : "2026-06-15T23:25:02.616", "createdAt" : "2026-06-15T23:25:02.616", "lastUpdated" : "2026-06-16T07:35:33.194", "ingestTimestamp" : "2026-06-15T23:25:02.616", "mongoId" : "6a306073f292fd229cf8dc7c", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 12480, "salaryAnnualMax" : 41600, "salaryBand" : "<30k", "hasSalary" : true, "allSkills" : [ "Pavement condition assessment", "Pavement distress identification", "Pavement rating criteria", "PCI surveys", "Pavement distress", "Condition assessment", "Pavement Condition Index (PCI)", "Pavement distress types", "Pavement severity levels", "Pavement condition ratings", "Roadway imagery analysis", "Infrastructure maintenance planning" ], "skillCount" : 12, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.92 }, { "id" : "6a306073f292fd229cf8dc7b", "title" : "Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project", "company" : "Meridial", "salary" : { "min" : 6.0, "max" : 20.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Worldwide - Remote", "locations" : [ "Worldwide - Remote" ], "timestamp" : "2026-06-16T07:21:32.621", "fingerprint" : "e2ee0dd398fa5552aa2631a45c5b7b6922bb62d45e8289fbf952a320331c64ab", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/agency/jobs/4781823101", "externalId" : "4781823101", "industryFunction" : { }, "structuredLocations" : [ { "workMode" : "remote" } ], "locationText" : "", "employmentType" : "CONTRACT", "hardSkillsList" : [ "Pavement condition assessment", "Pavement distress identification" ], "hardSkills" : [ { "name" : "Pavement condition assessment", "level" : "intermediate" }, { "name" : "Pavement distress identification", "level" : "intermediate" } ], "majorSkills" : "PCI surveys, Roadway inspection", "majorSkillsList" : [ "PCI surveys", "Roadway inspection" ], "coreResponsibilities" : "Review roadway images, Review inspection records, Review AI-generated outputs, Determine accuracy of distress types, Determine accuracy of severity levels, Determine accuracy of condition assessments, Annotate pavement features, Validate pavement features, Annotate pavement distress patterns, Validate pavement distress patterns, Analyze roadway imagery, Analyze survey excerpts, Validate AI-generated classifications, Provide written feedback, Clarify inspector distinctions, Clarify sampling unit evaluation, Clarify real-world condition influence", "domainKnowledge" : "Pavement Condition Index (PCI); Pavement distress types; Pavement severity levels; Pavement condition ratings; Cracking; Rutting; Spalling; Patching; Weathering", "domainList" : [ "pavement-condition-index-pci", "pavement-distress-types", "pavement-severity-levels", "pavement-condition-ratings", "cracking", "rutting", "spalling", "patching", "weathering" ], "domainSpecificKnowledge" : [ "Pavement Condition Index (PCI)", "Pavement distress types", "Pavement severity levels", "Pavement condition ratings", "Cracking", "Rutting", "Spalling", "Patching", "Weathering" ], "communicationSkills" : "Written feedback; Structured explanation", "qualificationsBasic" : "Familiarity with PCI surveys, Attention to visual detail, Ability to apply distress definitions, Ability to apply rating criteria, Clear written communication, Ability to explain inspection reasoning, Ability to explain classification decisions", "qualificationsPreferred" : "Experience working with inspection imagery, Experience with condition reports, Experience with roadway maintenance planning", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Are you a pavement professional or roadway inspector with hands-on experience conducting or interpreting Pavement Condition Index (PCI) surveys? Advanced AI systems are being developed to understand roadway conditions, interpret inspection imagery, and support infrastructure maintenance planning. High-quality training data based on real PCI survey practices is essential to ensure these systems accurately recognize pavement distress and condition ratings. This project relies on your expertise to help train and evaluate next-generation AI models. In this project, you will focus specifically on PCI-related workflows and annotation tasks. You will review roadway images, inspection records, and AI-generated outputs to determine whether pavement distress types, severity levels, and condition assessments are accurate and consistent with PCI methodology. A central part of the work involves annotating or validating pavement features and distress patterns so models can better learn to identify cracking, rutting, spalling, patching, weathering, and other common pavement conditions. On a typical day, you may analyze roadway imagery or survey excerpts, validate AI-generated classifications of pavement distress, and provide written feedback explaining where models misidentify features or misinterpret severity levels. You may also help clarify how inspectors distinguish between similar distress categories, how sampling units are evaluated, and how real-world field conditions influence PCI scoring and reporting. This project is well suited for pavement engineers, civil or transportation engineers, DOT specialists, highway inspectors, and other professionals who have conducted or reviewed PCI surveys or pavement condition assessments. Experience working with inspection imagery, condition reports, or roadway maintenance planning is highly valuable. Clear written communication and the ability to explain inspection reasoning and classification decisions in a structured way are essential. No prior AI or technical background is required. Training and project guidelines will be provided. What matters most is your familiarity with PCI surveys, attention to visual detail, and ability to consistently apply pavement distress definitions and rating criteria. We offer a pay range of $6 - $20 per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above. As a contractor, you will supply a secure computer and high-speed internet; company-sponsored benefits such as health insurance and PTO do not apply. Job title: Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project Employment type: Freelance / Contract Workplace type: Remote", "summaryDescription" : "Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project at Meridial. Skills: PCI surveys, Roadway inspection. Review roadway images. Review inspection records", "postedDate" : "2026-06-15T23:23:33.442", "createdAt" : "2026-06-15T23:23:33.442", "lastUpdated" : "2026-06-16T07:21:32.621", "ingestTimestamp" : "2026-06-15T23:23:33.442", "mongoId" : "6a306073f292fd229cf8dc7b", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 12480, "salaryAnnualMax" : 41600, "salaryBand" : "<30k", "hasSalary" : true, "allSkills" : [ "Pavement condition assessment", "Pavement distress identification", "PCI surveys", "Roadway inspection", "Pavement Condition Index (PCI)", "Pavement distress types", "Pavement severity levels", "Pavement condition ratings", "Cracking", "Rutting", "Spalling", "Patching", "Weathering" ], "skillCount" : 13, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.92 }, { "id" : "6a306073f292fd229cf8dc79", "title" : "Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project", "company" : "Meridial", "salary" : { "min" : 6.0, "max" : 20.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Worldwide - Remote", "locations" : [ "Worldwide - Remote" ], "timestamp" : "2026-06-16T06:46:20.672", "fingerprint" : "76732f1da2ed3bcd49f65042a09b5bd2fda9e500784faa3ced4b805762bb45a8", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/agency/jobs/4781825101", "externalId" : "4781825101", "industryFunction" : { }, "structuredLocations" : [ { "workMode" : "remote" } ], "locationText" : "", "employmentType" : "CONTRACT", "hardSkillsList" : [ "PCI surveys", "Pavement condition assessment" ], "hardSkills" : [ { "name" : "PCI surveys", "level" : "intermediate" }, { "name" : "Pavement condition assessment", "level" : "intermediate" } ], "majorSkills" : "PCI surveys, Pavement condition assessment", "majorSkillsList" : [ "PCI surveys", "Pavement condition assessment" ], "coreResponsibilities" : "Review roadway images, Review inspection records, Review AI-generated outputs, Determine accuracy of distress types, Determine accuracy of severity levels, Determine accuracy of condition assessments, Annotate pavement features, Validate pavement features, Annotate distress patterns, Validate distress patterns, Analyze roadway imagery, Analyze survey excerpts, Validate AI-generated classifications, Provide written feedback, Explain where models misidentify features, Explain where models misinterpret severity, Clarify inspector distinctions between categories, Clarify how sampling units are evaluated, Clarify how field conditions influence scoring, Clarify how field conditions influence reporting", "domainKnowledge" : "Pavement Condition Index (PCI); Pavement distress types; Pavement severity levels; Pavement condition ratings; Cracking; Rutting; Spalling; Patching; Weathering; Roadway conditions; Infrastructure maintenance planning", "domainList" : [ "pavement-condition-index-pci", "pavement-distress-types", "pavement-severity-levels", "pavement-condition-ratings", "cracking", "rutting", "spalling", "patching", "weathering", "roadway-conditions", "infrastructure-maintenance-planning" ], "domainSpecificKnowledge" : [ "Pavement Condition Index (PCI)", "Pavement distress types", "Pavement severity levels", "Pavement condition ratings", "Cracking", "Rutting", "Spalling", "Patching", "Weathering", "Roadway conditions", "Infrastructure maintenance planning" ], "communicationSkills" : "Written communication; Explain inspection reasoning; Explain classification decisions", "qualificationsBasic" : "Familiarity with PCI surveys, Attention to visual detail, Ability to apply distress definitions, Ability to apply rating criteria", "qualificationsPreferred" : "Experience with inspection imagery, Experience with condition reports, Experience with roadway maintenance planning", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Are you a pavement professional or roadway inspector with hands-on experience conducting or interpreting Pavement Condition Index (PCI) surveys? Advanced AI systems are being developed to understand roadway conditions, interpret inspection imagery, and support infrastructure maintenance planning. High-quality training data based on real PCI survey practices is essential to ensure these systems accurately recognize pavement distress and condition ratings. This project relies on your expertise to help train and evaluate next-generation AI models. In this project, you will focus specifically on PCI-related workflows and annotation tasks. You will review roadway images, inspection records, and AI-generated outputs to determine whether pavement distress types, severity levels, and condition assessments are accurate and consistent with PCI methodology. A central part of the work involves annotating or validating pavement features and distress patterns so models can better learn to identify cracking, rutting, spalling, patching, weathering, and other common pavement conditions. On a typical day, you may analyze roadway imagery or survey excerpts, validate AI-generated classifications of pavement distress, and provide written feedback explaining where models misidentify features or misinterpret severity levels. You may also help clarify how inspectors distinguish between similar distress categories, how sampling units are evaluated, and how real-world field conditions influence PCI scoring and reporting. This project is well suited for pavement engineers, civil or transportation engineers, DOT specialists, highway inspectors, and other professionals who have conducted or reviewed PCI surveys or pavement condition assessments. Experience working with inspection imagery, condition reports, or roadway maintenance planning is highly valuable. Clear written communication and the ability to explain inspection reasoning and classification decisions in a structured way are essential. No prior AI or technical background is required. Training and project guidelines will be provided. What matters most is your familiarity with PCI surveys, attention to visual detail, and ability to consistently apply pavement distress definitions and rating criteria. We offer a pay range of $6 - $20 per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above. As a contractor, you will supply a secure computer and high-speed internet; company-sponsored benefits such as health insurance and PTO do not apply. Job title: Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project Employment type: Freelance / Contract Workplace type: Remote", "summaryDescription" : "Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project at Meridial. Skills: PCI surveys, Pavement condition assessment. Review roadway images. Review inspection records", "postedDate" : "2026-06-15T23:22:01.603", "createdAt" : "2026-06-15T23:22:01.603", "lastUpdated" : "2026-06-16T06:46:20.672", "ingestTimestamp" : "2026-06-15T23:22:01.603", "mongoId" : "6a306073f292fd229cf8dc79", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 12480, "salaryAnnualMax" : 41600, "salaryBand" : "<30k", "hasSalary" : true, "allSkills" : [ "PCI surveys", "Pavement condition assessment", "Pavement Condition Index (PCI)", "Pavement distress types", "Pavement severity levels", "Pavement condition ratings", "Cracking", "Rutting", "Spalling", "Patching", "Weathering", "Roadway conditions", "Infrastructure maintenance planning" ], "skillCount" : 13, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.92 }, { "id" : "6a3066c2f292fd229cfb56ca", "title" : "Data Delivery Specialist", "company" : "Sprinter", "industry" : "Retail", "salary" : { "min" : 30000.0, "max" : 42000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Data Delivery Specialist in Alicante, Spain, adjusted for the retail industry and company size." }, "location" : "Avenida del Euro n. 2 - 03114 Alicante", "locations" : [ "Avenida del Euro n. 2 - 03114 Alicante" ], "timestamp" : "2026-06-16T09:03:19.646", "fingerprint" : "218e96e30052e50db0695c01b4becb2cfbd6eda800551507ced1d1567964d642", "source" : "greenhouse", "language" : "es", "applyUrl" : "https://job-boards.eu.greenhouse.io/sprintersportses/jobs/4898369101", "externalId" : "4898369101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Alicante", "country" : "Spain", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "38.3436365,-0.4881708" } ], "locationText" : "Alicante, Spain", "minimumEducation" : "Bachelor's", "experienceMinYears" : 3, "experienceMaxYears" : 5, "experienceLevel" : "Mid", "technicalSkills" : "JIRA Service Management, Jira Software", "professionalSkills" : [ "Gestión de Stakeholders", "Gestión de Negocio", "Capacidad Analítica", "Comunicación ecosistema IT" ], "hardSkillsList" : [ "Gestión de demanda", "Metodologías Ágiles", "Kanban", "Scrum", "Gestión del Flujo", "Reporting de rendimiento", "SLAs" ], "hardSkills" : [ { "name" : "Gestión de demanda", "level" : "intermediate" }, { "name" : "Metodologías Ágiles", "level" : "intermediate" }, { "name" : "Kanban", "level" : "intermediate" }, { "name" : "Scrum", "level" : "intermediate" }, { "name" : "Gestión del Flujo", "level" : "intermediate" }, { "name" : "Reporting de rendimiento", "level" : "intermediate" }, { "name" : "SLAs", "level" : "intermediate" } ], "majorSkills" : "Data Delivery, Agile Methodologies, Stakeholder Management, JIRA", "majorSkillsList" : [ "Data Delivery", "Agile Methodologies", "Stakeholder Management", "JIRA" ], "coreResponsibilities" : "Orquestar y optimizar el flujo de demanda, Garantizar una entrega impecable y ágil, Gestionar el ciclo de vida de las peticiones, Centralizar y refinar peticiones vía JIRA, Gestionar el Backlog global, Articular el flujo entre áreas, Documentar procesos, Comunicar procesos, Implementar marcos Kanban, Liderar marcos Sprints Agile, Adaptar metodologías a necesidades, Coordinar con líderes técnicos, Eliminar bloqueos, Optimizar la velocidad del equipo, Administrar el backlog, Priorizar tareas, Articular demanda técnica, Articular demanda de negocio, Gestionar usuarios de negocio, Gestionar expectativas de entrega, Incluir usuarios en ciclo de vida, Gestionar dependencias, Gestionar riesgos, Gestionar bloqueos, Elaborar informes de nivel de servicio, Medir la salud del equipo, Medir el rendimiento del equipo", "teamCollaboration" : "Coordinar con líderes técnicos; Coordinar dependencias; Alinear planes de entrega; Colaborar con áreas de IT", "projectManagementSkills" : [ "Agile", "Kanban", "Scrum", "Backlog management", "Prioritization" ], "domainKnowledge" : "Servicios de datos; Gobierno de datos; Arquitectura de datos; IA; Ingeniería de datos; Visualización de datos", "domainList" : [ "servicios-de-datos", "gobierno-de-datos", "arquitectura-de-datos", "ia", "ingenieria-de-datos", "visualizacion-de-datos" ], "domainSpecificKnowledge" : [ "Servicios de datos", "Gobierno de datos", "Arquitectura de datos", "IA", "Ingeniería de datos", "Visualización de datos" ], "toolProficiency" : [ "JIRA Service Management", "Jira Software" ], "communicationSkills" : "Comunicar procesos; Comunicar estándares; Comunicar planes de entrega", "documentationSkills" : "Documentar procesos; Documentar procedimientos; Documentar estándares", "continuousLearning" : "Plan de desarrollo personalizado; Carrera internacional; Amplio catálogo formativo", "problemSolvingSkills" : "Eliminar bloqueos; Resolver dependencias; Resolver riesgos; Resolver bloqueos", "outcomesObjectives" : "Garantizar entrega impecable; Garantizar entrega ágil; Asegurar trabajo en lo que mueve aguja; Optimizar velocidad del equipo; Medir salud del equipo; Medir rendimiento del equipo", "qualificationsBasic" : "Grado en Ingeniería Informática, Matemáticas o similar, 3-5 años en gestión de entregas (delivery), Gestión de servicios IT y/o Proyectos, Gestión directa de usuarios clave de negocio, Capacidad para gestionar prioridades, Capacidad para traducir conceptos de negocio en términos técnicos, Capacidad para coordinar dependencias, Alinear planes de entrega con otras áreas de IT, Experto en JIRA Service Management, Experto en Jira Software, Inglés B2", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certs", "workSiteFlexibility" : "Flexible", "rawDescription" : "Como Data Delivery Specialist, serás el responsable de orquestar y optimizar el flujo de demanda de nuestro servicio de datos (Gobierno, Arquitectura, IA, Ingeniería y Visualización). Tu objetivo es garantizar una entrega impecable y ágil, gestionando el ciclo de vida de las peticiones desde su entrada en JIRA hasta su puesta en valor para negocio. En tu día a día: Orquestación de la Demanda: Gestionar el proceso end-to-end de recepción, análisis, priorización y seguimiento de demandas de negocio hacia el equipo de IT DATA. Centralizar y refinar todas las peticiones que entran vía JIRA del ámbito IT DATA para que recojan la información relevante para su posterior análisis por el equipo. Gestionar el Backlog global, asegurando que el equipo trabaje en lo que realmente mueve la aguja para el negocio. Articular el flujo entre las áreas de Gobierno, Arquitectura/IA, Ingeniería y Visualizació n. Documentar y comunicar los procesos, procedimientos y estándares de gestión de la demanda. Liderazgo de Metodología (Agile & Flow): Metodologías Ágiles: Implementación y liderazgo de marcos Kanban y Sprints Agile, adaptándolos a las necesidades de mantenimiento incidental y proyectos evolutivos. Coordinar con los líderes técnicos para eliminar bloqueos/dependencias y optimizar la velocidad del equipo. Gestión del Flujo (JIRA): Administración del backlog, priorización de tareas y articulación de la demanda técnica y de negocio. Capacidad para gestionar usuarios de negocio (data owners y stewards) y sus expectativas de entrega, incluyéndolos en el ciclo de vida de la iniciativa Gestionar dependencias, riesgos y bloqueos asociados a las peticiones de productos de datos solicitados. KPIs de Performance: Elaboración de informes de nivel de servicio (SLA, Cycle Time, Velocity, Burndown Chart, Capacidad del equipo, Panel de Bloqueos) para medir la salud y el rendimiento del equipo. ¿Qué buscamos? Grado en Ingeniería Informática, Matemáticas o similar. Experiencia sólida (3-5 años) en la gestión de entregas (delivery) en entornos de servicios DATA y gestionando servicios IT y/o Proyectos. Gestión de Stakeholders y Negocio: Experiencia demostrable en la gestión directa de usuarios clave de negocio, con capacidad para gestionar prioridades en función del valor que aportan las necesidades al negocio y expectativas de entrega Capacidad Analítica: Capacidad para \"traducir\" conceptos de negocio en términos técnicos de arquitecturas data para elaborar planes de entrega claros para los usuarios de negocio. Comunicación ecosistema IT: Capacidad para coordinar dependencias y alinear planes de entrega con otras áreas de IT (Infraestructura, Seguridad, DevOps, etc..) Domino de Herramientas: Experto en JIRA Service Management y Jira Software (configuración de tableros, flujos de estado y reporting de rendimiento de equipo y SLAs). Agilidad: Conocimiento profundo de Scrum, Kanban y cómo adaptarlos a un entorno que mezcla desarrollo (proyectos) con soporte (incidentes). Inglés B2 ¿Qué podemos ofrecerte? Bonus anual según performance. Flexibilidad horaria. Retribución flexible (seguro médico, restaurant, transporte, guardería...). Descuento de empleado/ a. Plan de desarrollo personalizado y carrera en un entorno internacional (JD Group). Amplio catálogo formativo en hard y soft skills Instalaciones deportivas dentro de la empresa. Sobre el grupo: Abrimos nuestro primer Sprinter en Valencia en 1995 y, desde entonces, nos hemos convertido en el espacio para quienes sentimos pasión por el deporte y la moda deportiva. Con más de 200 puntos de venta físicos y tienda online, contamos con marcas referentes como Nike, Adidas, Reebok o Fila, y con marcas propias como Up, Silver, Doone y Boriken, entre otras. Formando parte de JD Group, líder en Sports, Street & Premium Fashion, contamos con alrededor de 97.000 personas, superando las 4850 tiendas de diversas marcas en más de 49 países. ¡Te damos la oportunidad de desarrollar tu carrera en este grupo internacional en constante crecimiento! En Sprinter ofrecemos un entorno basado en la cooperación y el respeto mutuo, con un fuerte compromiso por la diversidad y la igualdad de oportunidades. Todas las personas serán consideradas sin importar su identidad de género, orientación sexual, etnia, religión, edad o grado de discapacidad. Nuestros procesos de selección están basados en el modelo de evaluación por competencias profesionales y valoramos la pasión, ganas de aprender y de crecer en un entorno internacional. ¿Te interesa? ¡Queremos conocerte! Si crees que esta oferta es para ti, aplica hoy mismo. Debido al alto volumen de solicitudes que recibimos para nuestras ofertas, lleva un tiempo poder revisarlas todas. Si no recibes noticias dentro de las dos-tres semanas posteriores a tu solicitud, por favor considera que en esta ocasión hemos decidido avanzar con otras candidaturas. Las personas que cumplan con los criterios serán contactadas por el equipo de Talent. ¡Gracias por tu interés y tiempo!", "summaryDescription" : "Data Delivery Specialist at Sprinter. Skills: Data Delivery, Agile Methodologies, Stakeholder Management, JIRA. Orquestar y optimizar el flujo de demanda. Garantizar una entrega impecable y ágil", "postedDate" : "2026-06-15T23:28:17.709", "createdAt" : "2026-06-15T23:28:17.709", "lastUpdated" : "2026-06-16T09:03:19.646", "ingestTimestamp" : "2026-06-15T23:28:17.709", "mongoId" : "6a3066c2f292fd229cfb56ca", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "30k-50k", "hasSalary" : false, "allSkills" : [ "Gestión de demanda", "Metodologías Ágiles", "Kanban", "Scrum", "Gestión del Flujo", "Reporting de rendimiento", "SLAs", "Data Delivery", "Agile Methodologies", "Stakeholder Management", "JIRA", "Gestión de Stakeholders", "Gestión de Negocio", "Capacidad Analítica", "Comunicación ecosistema IT", "Agile", "Backlog management", "Prioritization", "Servicios de datos", "Gobierno de datos", "Arquitectura de datos", "IA", "Ingeniería de datos", "Visualización de datos", "JIRA Service Management", "Jira Software" ], "skillCount" : 26, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Retail", "llmIndustryConfidence" : 0.95 }, { "id" : "6a306021f292fd229cf8619a", "title" : "Clinical Data Specialist", "company" : "Iterative Health", "industry" : "Healthcare", "salary" : { "min" : 85000.0, "max" : 125000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "The estimated salary is based on the market baseline for a Clinical Data Specialist in Cambridge, United States, adjusted for mid-seniority and the healthcare industry." }, "location" : "Cambridge, Massachusetts, United States", "locations" : [ "Cambridge", "Massachusetts", "United States", "Dallas HQ", "New York", "New York", "United States" ], "timestamp" : "2026-06-16T07:50:02.004", "fingerprint" : "41ed16a45f5732b3e5ac6eadcdce4ab1f5128deee0fa2c57b2744365b2182d1d", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/iterativehealth/jobs/4687877006", "externalId" : "4687877006", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Cambridge", "state" : "Massachusetts", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "42.3656347,-71.1040018" } ], "locationText" : "Cambridge, Massachusetts, United States", "employmentType" : "FULL_TIME", "technicalSkills" : "EHR, CTMS, CRM", "professionalSkills" : [ "Clinical documentation", "Patient recruitment", "Data management", "Operational coordination" ], "hardSkillsList" : [ "Data entry", "Database maintenance" ], "hardSkills" : [ { "name" : "Data entry", "level" : "intermediate" }, { "name" : "Database maintenance", "level" : "intermediate" } ], "majorSkills" : "Clinical research, Data analysis, Patient identification", "majorSkillsList" : [ "Clinical research", "Data analysis", "Patient identification" ], "coreResponsibilities" : "Review electronic health records, Identify patients for studies, Interpret study protocols, Interpret eligibility criteria, Determine appropriate patient populations, Build databases of participants, Maintain databases of participants, Document patient pre-screening activities, Document pre-screening findings, Collaborate with research sites, Collaborate with clinical teams, Support participant recruitment, Support research sites, Collect data, Document data, Coordinate operational activities, Assist with scheduling patient visits, Coordinate research appointments, Perform data entry, Maintain study records, Maintain tracking tools, Participate in project meetings, Contribute to process improvement", "teamCollaboration" : "Research sites; Clinical teams", "domainKnowledge" : "Clinical trials; Healthcare technology; Good Clinical Practice; Protected health information", "domainList" : [ "clinical-trials", "healthcare-technology", "good-clinical-practice", "protected-health-information" ], "domainSpecificKnowledge" : [ "Clinical trials", "Healthcare technology", "Good Clinical Practice", "Protected health information" ], "toolProficiency" : [ "Microsoft Office Suite", "Google Workspace", "Adobe Acrobat", "Salesforce", "CTMS platforms" ], "communicationSkills" : "Written communication; Verbal communication", "documentationSkills" : "Accurate documentation; Study documentation; Data documentation", "qualificationsBasic" : "Bachelor's degree or equivalent, Proficiency with Microsoft Office Suite, Proficiency with Google Workspace, Proficiency with Adobe Acrobat, Proficiency with web-based applications, Ability to learn new technology platforms, Exceptional attention to detail, Organizational skills, Time management skills, Ability to manage multiple priorities, Excellent written communication skills, Excellent verbal communication skills, Ability to work independently, Ability to work collaboratively, High degree of professionalism, High degree of discretion, High degree of integrity", "qualificationsPreferred" : "Prior experience in clinical research, Prior experience in healthcare operations, Prior experience in patient recruitment, Prior experience in data management, Familiarity with clinical research protocols, Familiarity with eligibility criteria, Experience reviewing EHR data, Experience interpreting EHR data, Knowledge of GCP guidelines, Knowledge of clinical research regulations, Experience in healthcare technology, Experience in biotech, Experience in a startup environment, Familiarity with Salesforce, Familiarity with CTMS platforms, Familiarity with research technology systems", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Iterative Health is a healthcare technology and services company powering the acceleration of clinical research to transform patient outcomes. The Iterative Health Site Network is a premier network of 100+ clinical research sites across the US and Europe, accelerating the path to market for novel therapies. By combining deep expertise in clinical trials with cutting-edge AI, we empower research teams and study sponsors to expand and expedite access to novel therapeutics for patients in need. About Iterative Health At Iterative Health, we are transforming clinical research through the power of AI, technology, and human expertise. Iterative Health is a healthcare technology and services company powering the acceleration of clinical research to improve patient outcomes. Through the Iterative Health Site Network — a premier network of 100+ clinical research sites across the US and Europe — we help expand and expedite access to novel therapeutics for patients in need. Why This Role Matters The Clinical Data Specialist at Iterative Health plays a critical role in supporting clinical trial operations across the Iterative Health research network. This position is responsible for conducting detailed EHR reviews to identify potential clinical trial candidates, supporting patient recruitment efforts, maintaining research databases, and ensuring accurate documentation throughout the patient pre-screening process. The ideal candidate is highly detail-oriented, thrives in a fast-paced environment, and is passionate about advancing clinical research through data-driven patient identification and operational excellence. Where You’ll Drive Impact Clinical Trial Patient Identification & Screening Review electronic health records (EHRs) to identify patients who may qualify for active clinical research studies. Interpret study protocols and eligibility criteria to determine appropriate patient populations for recruitment. Build and maintain databases of potential study participants across multiple research programs. Document patient pre-screening activities and findings in accordance with established procedures and regulatory requirements. Collaborate with research sites and clinical teams to support participant recruitment initiatives. Research Operations Support Support research sites within the Iterative Health network through data collection, documentation, and operational coordination activities. Assist with scheduling patient visits and coordinating research-related appointments. Perform accurate and timely data entry into clinical research databases and internal systems. Maintain study-related records and tracking tools to support operational efficiency and reporting needs. Participate in project meetings and contribute to ongoing process improvement initiatives. Compliance & Quality Handle protected health information (PHI) and research data in a confidential, compliant, and secure manner. Adhere to company policies, study protocols, Good Clinical Practice (GCP) guidelines, and applicable regulatory requirements. Ensure accuracy, completeness, and quality of all documentation and data-related activities. What You Bring to the Team Bachelor's degree or equivalent combination of education and experience. Proficiency with Microsoft Office Suite (Word, Excel, PowerPoint), Google Workspace (Docs, Sheets, Drive, Gmail), Adobe Acrobat, and web-based applications. Ability to quickly learn and navigate new technology platforms, including Electronic Health Records (EHRs), Clinical Trial Management Systems (CTMS), and Customer Relationship Management (CRM) tools. Exceptional attention to detail and organizational skills. Strong time management skills with the ability to manage multiple priorities simultaneously. Excellent written and verbal communication skills. Demonstrated ability to work independently and collaboratively in a dynamic, fast-paced environment. High degree of professionalism, discretion, and integrity when handling sensitive information. Preferred Qualifications Prior experience in clinical research, healthcare operations, patient recruitment, or data management. Familiarity with clinical research protocols and eligibility criteria. Experience reviewing and interpreting electronic health record data. Knowledge of Good Clinical Practice (GCP) guidelines and clinical research regulations. Experience working within a healthcare technology, biotech, or startup environment. Familiarity with Salesforce, CTMS platforms, or similar research technology systems. How We Work Collaborative and low-ego team environment High ownership and accountability culture Fast-paced and highly iterative growth environment Open communication and continuous learning mindset Mission-driven organization focused on improving patient outcomes Comfortable navigating evolving business priorities and opportunities Benefits That Support You We believe great teams do their best work when they feel supported — professionally and personally. Hybrid work environment with in-office collaboration two days per week in either our NYC or Boston office Comprehensive medical, dental, and vision coverage, with up to 80% of premiums covered by Iterative Health Mental health and wellness support through Spring Health Health HSA or FSA options, and commuter FSA contributions supported by Iterative Health Unlimited PTO, 12 company holidays, and a company-wide shutdown between Christmas and New Years 401(k) program with a company match of up to 3% (up to $3,000 annually) Weekly in-office lunch benefit every Tuesday 100% company-paid short-term and long-term disability coverage Annual wellness and professional development stipend to support your health and growth And more! At Iterative Health, we’re actively working towards creating an environment that is representative of the diversity of patients our technology serves. We are focused on building an equitable and inclusive culture, and by extension, hiring process. If you require any accommodations to make the application process or interviewing experience more accessible to you, please contact CandidateAccommodations@iterative.health.", "summaryDescription" : "Clinical Data Specialist at Iterative Health. Skills: Clinical research, Data analysis, Patient identification. Review electronic health records. Identify patients for studies", "postedDate" : "2026-06-15T23:23:01.338", "createdAt" : "2026-06-15T23:23:01.338", "lastUpdated" : "2026-06-16T07:50:02.004", "ingestTimestamp" : "2026-06-15T23:23:01.338", "mongoId" : "6a306021f292fd229cf8619a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 85000, "salaryAnnualMax" : 125000, "salaryBand" : "75k-100k", "hasSalary" : true, "allSkills" : [ "Data entry", "Database maintenance", "Clinical research", "Data analysis", "Patient identification", "Clinical documentation", "Patient recruitment", "Data management", "Operational coordination", "Clinical trials", "Healthcare technology", "Good Clinical Practice", "Protected health information", "Microsoft Office Suite", "Google Workspace", "Adobe Acrobat", "Salesforce", "CTMS platforms" ], "skillCount" : 18, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.95 }, { "id" : "6a306078f292fd229cf8e693", "title" : "Product Data Specialist", "company" : "LG Electronics", "salary" : { "min" : 75000.0, "max" : 105000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Product Data Specialist in Alpharetta, United States, adjusted for the technology industry and company size." }, "location" : "Alpharetta, GA", "locations" : [ "Alpharetta", "GA" ], "timestamp" : "2026-06-16T06:22:32.751", "fingerprint" : "b64073ed4d0c895c18ccc7928b0f1daf8d1a72f77123a0b3c48be94b6f8482fe", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/lgelectronics/jobs/5257778008", "externalId" : "5257778008", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Alpharetta", "state" : "Georgia", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "34.0755962,-84.2945964" } ], "locationText" : "Alpharetta, Georgia, United States", "minimumEducation" : "Bachelor's", "remoteFriendly" : false, "rawDescription" : "Step into the innovative world of LG Electronics. As a global leader in technology, LG Electronics is dedicated to creating innovative solutions for a better life. Our brand promise, 'Life's Good', embodies our commitment to ensuring a happier life for all. We have a rich history spanning over six decades and a global presence in over 290 locations. Our diverse portfolio includes Home Appliance Solutions, Media Entertainment Solutions, Vehicle Solutions, and Eco Solutions. Our management philosophy, \"Jeong-do Management,\" embodies our commitment to high ethical standards and transparent operations. Grounded in the principles of 'Customer-Value Creation' and 'People-Oriented Management', these values shape our corporate culture, fostering creativity, diversity, and integrity. At LG, we believe in the power of collective wisdom through an inclusive work environment. Join us and become a part of a company that is shaping the future of technology. At LG, we strive to make Life Good for Everyone. The Opportunity: Location will be in Alpharetta, GA Ensure consistency and accuracy of data across Product Information Management (PIM) and Digital Asset Management (DAM) systems. Support the RAG (Retrieval-Augmented Generation) database by ensuring documents are properly indexed, retrievable, and aligned with user queries. Manage and organize documents in the database, including submittals, owner manuals, engineering manuals, installation manuals, service manuals, and other relevant technical documents. Review new documents, classify them into appropriate categories, and ensure proper metadata and tagging for efficient retrieval. Maintain data quality by updating, correcting, or removing outdated or inaccurate content in the database. Monitor customer feedback and usage patterns to identify gaps or improvement areas in the database content. Collaborate with technical and support teams to validate document accuracy and relevance. Participate in periodic data quality audits and database optimization reviews. Document processes, changes, and best practices for ongoing database management and continuous improvement. Qualifications: Bachelor’s degree in a relevant field (e.g., Information Management, Engineering, Computer Science, or related discipline), or equivalent education and/or experience. Basic understanding of data management principles, including data accuracy, consistency, and organization. Familiarity with Product Information Management (PIM) or Digital Asset Management (DAM) systems (hands-on experience a plus, not required). Basic experience with databases or structured data, such as using Excel, Google Sheets, or simple database tools. Strong attention to detail and ability to follow detailed instructions. Effective written and verbal communication skills, with the ability to collaborate in a team environment. Proficiency in Microsoft Office (Word, PowerPoint, Excel, Outlook). Strong organizational skills and ability to manage multiple tasks in a fast-paced environment Recruiting Range $29—$29 USD Benefits Offered Full-Time Employees: No-cost employee premiums for you and your eligible dependents for competitive medical, dental, vision and prescription benefits. Auto enrollment with immediate vesting of competitive company matching contributions in a 401(k) Retirement Savings Plan with several investment options. Generous Paid Time Off program that includes company holidays and a combined bank of paid sick and vacation time. Performance based Short-Term Incentives (varies by role). Access to confidential mental health resources to help you and your loved ones improve your quality of life. Personal fitness goal incentives. Family orientated benefits such as paid parental leave and support for families raising children with learning, social, behavioral challenges, or developmental disabilities. Group Rate Life and Disability Insurance. Benefits Offered Temporary/Contractors: Eligible for the relevant benefit programs offered through our partner agencies. Privacy Notice to California Applicants Applicants who need assistance or a reasonable accommodation during the hiring process may contact our team by phone at: 973-477-7090 or support@lg4me.freshdesk.com. This email and phone number will only reply to accommodation requests and is not intended for general employment inquiries. All qualified applicants will be considered for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable federal, state, or local law. In addition to the above, LG believes that pay transparency is a key part of diversity, equity, and inclusion. Our salary ranges take into account many factors in making compensation decisions including but not limited to skillset, experience, licensure, certifications, internal equity, and other business needs. While we consider geographic pay differentials in final offers, because we operate in many geographies where applicable, the salary range listed may not reflect all geographic differentials applied.", "summaryDescription" : "Product Data Specialist at LG Electronics", "postedDate" : "2026-06-15T23:25:25.892", "createdAt" : "2026-06-15T23:25:25.892", "lastUpdated" : "2026-06-16T06:22:32.751", "ingestTimestamp" : "2026-06-15T23:25:25.892", "mongoId" : "6a306078f292fd229cf8e693", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 75000, "salaryAnnualMax" : 105000, "salaryBand" : "75k-100k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.6666667, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a3056b3f292fd229cf2d4c2", "title" : "Speech Language Pathologist", "company" : "BAYADA Home Health Care", "industry" : "Healthcare", "salary" : { "min" : 80.0, "max" : 90.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Field", "locations" : [ "Field", "Home Health - Field" ], "timestamp" : "2026-06-16T08:33:00.677", "fingerprint" : "e0013674a46e98928bcdcc605ea69ae24a8b7824869e208bf872e8f0fca38c3e", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/bayada/jobs/8592627002", "externalId" : "8592627002", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Milton", "state" : "Pennsylvania", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "41.0177269,-76.8530840" }, { "city" : "Mifflinburg", "state" : "Pennsylvania", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.9175820,-77.0477501" }, { "city" : "Selinsgrove", "state" : "Pennsylvania", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7993524,-76.8619072" }, { "city" : "Beavertown", "state" : "Pennsylvania", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7536190,-77.1693212" } ], "locationText" : "Milton, Pennsylvania, United States; Mifflinburg, Pennsylvania, United States; Selinsgrove, Pennsylvania, United States; Beavertown, Pennsylvania, United States", "experienceMinYears" : 1, "rawDescription" : "Make an Impact as a Speech Language Pathologist at BAYADA Home Health Care. BAYADA Home Health Care is currently seeking a Speech Language Pathologist (SLP) to join our Big Island Visits team. SLP’s work with clients in their home, craft treatment plans, and apply innovative techniques to help them reach their goals. You will be an integral member of a multi-disciplinary health care team that provides skilled nursing and rehabilitative care to clients, affording them the opportunity to remain at home. We believe our clients and their families deserve the highest quality home health care delivered with compassion, excellence, and reliability. Delivering this care is our highest priority and greatest joy. We want you to join us! How You’ll Make an Impact: Perform thorough evaluations to assess, diagnose and provide therapeutic interventions for clients who are experiencing, speech, language, communication or swallowing difficulties Develop a treatment plan based on the evaluation, physician’s orders and recommended goals Continually assess and revise the speech therapy care plan and participate with BAYADA Clinicians in the multidisciplinary care plan, as appropriate Educate and instruct patients, family members, or other patient representatives, in rehabilitative care and activities necessary to promote the client's health, safety and independent living Accurately document observations, interventions and evaluations pertaining to patient care management and services provided, utilizing a state-of-the-art touch pad tablet Compensation referral bonuses Paid Time Off: PTO (paid time off) and paid holidays Reimbursements: Mileage reimbursement or schedule-specific benefits Life Insurance: Employer-paid life insurance Wellness: Employee Assistance Program (EAP) Qualifications for a BAYADA Speech Language Pathologist: A current license as a Speech Language Pathologist in Hawaii One year experience as a Speech Language Pathologist Thrive in a Culture That Cares: We put your well-being first, fostering an inclusive and collaborative environment of belonging where you can achieve your goals. Don't just take our word for it: Voted by Star-Advertiser Readers as the #1 Non-Medical Home Care Provider   Forbes Top 10 Employer in Hawaii, 3 years in a row  Newsweek's Greatest Workplace for Overall, Women, Parents & Families, Diversity Forbes Best Employers for Veterans Be part of a caring, professional team that is instrumental in providing the highest quality care while developing your career with an industry leader. Apply now for immediate consideration. As a BAYADA Speech Language Pathologist you will be prepared to succeed. Paid training from day one in the office, in the home, and online to make sure you feel confident. Clinical support whenever you need it around the clock. BAYADA recognizes and rewards our SLPs who set and maintain the highest standards of excellence. We can’t wait to meet you! Locations We’re Hiring: Hilo, Hawaii Type: Per Diem Base Pay, depending upon qualifications and subject to negotiation: $80-$90 per point As an accredited, regulated, certified, and licensed home health care provider, BAYADA complies with all state/local mandates. BAYADA is celebrating 50 years of compassion, excellence, and reliability. Learn more about our 50th anniversary celebration and how you can join in here. BAYADA Home Health Care, Inc., and its associated entities and joint venture partners, are Equal Opportunity Employers. All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, age, disability, pregnancy or maternity, sexual orientation, gender identity, citizenship status, military status, or any other similarly protected status in accordance with federal, state and local laws. Hence, we strongly encourage applications from people with these identities or who are members of other marginalized communities.", "summaryDescription" : "Speech Language Pathologist at BAYADA Home Health Care", "postedDate" : "2026-06-15T23:19:47.007", "createdAt" : "2026-06-15T23:19:47.007", "lastUpdated" : "2026-06-16T08:33:00.677", "ingestTimestamp" : "2026-06-15T23:19:47.007", "mongoId" : "6a3056b3f292fd229cf2d4c2", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMax" : 90, "salaryBand" : "<30k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "healthcare", "jobSubcategory" : "support", "seniorityLevel" : "Mid", "dataQualityScore" : 0.6666667, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.98 }, { "id" : "693072a570f0b99d58ffb6eb", "title" : "Amazon Robotics Annotation Analyst", "company" : "Amazon Support Services Costa Rica SRL", "industry" : "Administrative Support, Planning/Development, Logistics", "salary" : { "min" : 1.4E7, "max" : 2.0E7, "currency" : "CRC", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "The estimation is based on the market baseline for a Mid-level Technology role in San Jose, Costa Rica, adjusted for company size and industry." }, "location" : "CRI", "locations" : [ "CRI" ], "timestamp" : "2026-06-15T01:32:11.737", "fingerprint" : "9301f4574a10785bc0f8d660dcfee5d62a2423540a04b45784d547e4bda59058", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3134225/apply", "externalId" : "cca5818e-bc4a-4d1d-aa6f-848218cd911e", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Costa Rica", "continent" : "na", "workMode" : "onsite" } ], "locationText" : "Costa Rica", "employmentType" : "FULL_TIME", "technicalSkills" : "SQL, Excel, Shell scripts", "professionalSkills" : [ "Data annotation", "AI/machine learning support", "Robotics operations", "Annotation standards", "Quality standards", "KPI definition" ], "hardSkillsList" : [ "Object segmentation", "Classification", "Written description", "Detection", "Troubleshooting techniques", "Validation scripts", "Process gap identification" ], "softSkillsList" : [ "Adaptability", "Curiosity" ], "hardSkills" : [ { "name" : "Object segmentation", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Written description", "level" : "intermediate" }, { "name" : "Detection", "level" : "intermediate" }, { "name" : "Troubleshooting techniques", "level" : "intermediate" }, { "name" : "Validation scripts", "level" : "intermediate" }, { "name" : "Process gap identification", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Adaptability" }, { "name" : "Curiosity" } ], "majorSkills" : "Data annotation, Robotics, AI model training", "majorSkillsList" : [ "Data annotation", "Robotics", "AI model training" ], "coreResponsibilities" : "Perform multi-modal data annotations, Collaborate with scientists and engineers to translate ambiguous, Conduct remote tele-planning and tele-operation activities to support, Define quality standards and key performance indicators (KPIs), Validate annotated data using troubleshooting techniques and validation, Analyze the relationship between ground truth data quality, Identify process gaps and improvement opportunities, Implement proactive measures to maintain high-quality output, Communicate project status, challenges, and recommendations to technical", "teamCollaboration" : "Collaborate with scientists and engineers; Communicate project status to technical teams and stakeholders", "domainKnowledge" : "Robotics; Artificial intelligence; Human-AI collaboration; Autonomous systems; Manipulation robotics; Mobile robotic systems", "domainList" : [ "robotics", "artificial-intelligence", "human-ai-collaboration", "autonomous-systems", "manipulation-robotics", "mobile-robotic-systems" ], "domainSpecificKnowledge" : [ "Robotics", "Artificial intelligence", "Human-AI collaboration", "Autonomous systems", "Manipulation robotics", "Mobile robotic systems" ], "toolProficiency" : [ "CVAT", "Labelbox", "SageMaker Ground Truth" ], "communicationSkills" : "Written reports; Presentations", "documentationSkills" : "Annotation standards; Standard operating procedures (SOPs); Best practices", "innovationCreativity" : "Create annotation standards; Define annotation approaches; Shape next-generation AI robotics", "problemSolvingSkills" : "Troubleshooting techniques; Process gap identification; Structured problem-solving", "specialRequirements" : "Travel to the United States approximately 1-2 times per year for one week per trip", "outcomesObjectives" : "Ensure accuracy and consistency of annotated data; Maintain high-quality output", "qualificationsBasic" : "Bachelor's Degree in Computer Science, Engineering, or related technical field, OR 3+ years of professional experience in data annotation, AI/machine learning support, or robotics operations, 2+ years of experience collaborating with science or engineering teams to define dataset requirements for training AI models and converting those requirements into standard operating procedures, 2+ years of experience performing multi-modal data annotations including object segmentation, classification, written description, and detection, 1+ years of experience defining quality standards and KPIs for data annotation projects, Experience with basic technical tools including Excel, SQL queries, reporting tools, and shell scripts, Experience working with both Windows and Mac operating systems, Demonstrated written and verbal communication skills in English, including the ability to deliver presentations to technical audiences, Experience working in ambiguous environments with minimal predefined structure", "qualificationsPreferred" : "Master's Degree in Computer Science, Engineering, or related technical field, Experience with remote tele-planning or tele-operation of robotic systems, Experience working with industry data labeling tools such as Computer Vision Annotation Tool (CVAT), Labelbox, or SageMaker Ground Truth, Familiarity with manipulation robotics and mobile robotic systems, Experience using structured problem-solving techniques such as five-whys analysis or root cause analysis, Understanding of testing methodologies such as A testing for dataset validation and performance evaluation, Experience configuring and using open-source tools to improve or validate ground truth data quality, Experience managing relationships with senior technical stakeholders across multiple teams, Track record of working independently with minimal direction in fast-paced, rapidly changing environments", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Are you ready to shape the future of robotics through human-AI collaboration? Join us in a role where your judgment and adaptability directly impact how Amazon's robotic systems learn and evolve. You'll work at the intersection of artificial intelligence and robotics, helping define how machines understand the world through your expert data annotations, remote tele-planning, and real-time operational support. This isn't traditional data labeling. You will collaborate with scientists and engineers on ambiguous, cutting-edge projects where standard procedures don't yet exist, and your insights will help create them. Key job responsibilities • Perform multi-modal data annotations including object segmentation, classification, written descriptions, and detection for robotics and AI model training • Collaborate with scientists and engineers to translate ambiguous technical requirements into clear annotation standards and standard operating procedures (SOPs) • Conduct remote tele-planning and tele-operation activities to support robotics systems development and testing • Define quality standards and key performance indicators (KPIs) for annotation projects where established procedures do not yet exist • Validate annotated data using troubleshooting techniques and validation scripts to ensure accuracy and consistency • Analyze the relationship between ground truth data quality and AI model performance metrics such as accuracy, precision, and false positive rates • Identify process gaps and improvement opportunities, then implement proactive measures to maintain high-quality output • Communicate project status, challenges, and recommendations to technical teams and stakeholders through written reports and presentations • Travel to the United States approximately 1-2 times per year for one week per trip A day in the life Your day starts reviewing new robotics tasks requiring annotation standards built from scratch. You'll collaborate with research scientists via video calls to understand model requirements, then design annotation approaches and quality metrics. Mid-morning, you might annotate complex robotic manipulation scenarios across video, image, or text data—providing the foundation that trains autonomous systems. Afternoons involve analyzing quality trends, identifying improvements, and documenting best practices for future scale. You'll alternate between focused annotation work on multi-modal data and collaborative problem-solving sessions where your expertise shapes next-generation AI robotics. The variety keeps every day engaging, with direct impact on robotic systems deployed across Amazon's network. About the team Amazon Robotics develops state-of-the-art robotics for Amazon's Fulfillment Network, which handles more individual items than any company in the world. We develop autonomously driving mobile robots and complex manipulation robots to solve real-world problems at scale. Within Amazon Robotics, the Global Operations - Artificial Intelligence (GO-AI) team enables Amazon to accelerate and scale our robotic and automation solutions through human supervisory control. We partner across Amazon's World Wide Operations organization to deliver data annotation services, ground truth data, and operational support that powers AI innovation. Our team thrives on solving ambiguous challenges, building processes where none exist, and maintaining the highest quality standards. We value curiosity, collaboration, and the ability to translate complex technical requirements into actionable workflows. As we expand our capabilities in remote operations and AI training, you'll help define what success looks like for this emerging field. Basic Qualifications: - Bachelor's Degree in Computer Science, Engineering, or related technical field, OR 3+ years of professional experience in data annotation, AI/machine learning support, or robotics operations - 2+ years of experience collaborating with science or engineering teams to define dataset requirements for training AI models and converting those requirements into standard operating procedures - 2+ years of experience performing multi-modal data annotations including object segmentation, classification, written description, and detection - 1+ years of experience defining quality standards and KPIs for data annotation projects - Experience with basic technical tools including Excel, SQL queries, reporting tools, and shell scripts - Experience working with both Windows and Mac operating systems - Demonstrated written and verbal communication skills in English, including the ability to deliver presentations to technical audiences - Experience working in ambiguous environments with minimal predefined structure Preferred Qualifications: - • Master's Degree in Computer Science, Engineering, or related technical field - • Experience with remote tele-planning or tele-operation of robotic systems - • Experience working with industry data labeling tools such as Computer Vision Annotation Tool (CVAT), Labelbox, or SageMaker Ground Truth - • Familiarity with manipulation robotics and mobile robotic systems - • Experience using structured problem-solving techniques such as five-whys analysis or root cause analysis - • Understanding of testing methodologies such as A/B testing for dataset validation and performance evaluation - • Experience configuring and using open-source tools to improve or validate ground truth data quality - • Experience managing relationships with senior technical stakeholders across multiple teams - • Track record of working independently with minimal direction in fast-paced, rapidly changing environments Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.", "summaryDescription" : "Amazon Robotics Annotation Analyst at Amazon Support Services Costa Rica SRL. Skills: Data annotation, Robotics, AI model training. Perform multi-modal data annotations. Collaborate with scientists and engineers to translate ambiguous", "postedDate" : "2026-06-13T01:15:29.835", "createdAt" : "2026-06-13T01:15:29.835", "lastUpdated" : "2026-06-15T01:32:11.737", "ingestTimestamp" : "2026-06-13T01:15:29.835", "mongoId" : "693072a570f0b99d58ffb6eb", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3134225/apply", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Object segmentation", "Classification", "Written description", "Detection", "Troubleshooting techniques", "Validation scripts", "Process gap identification", "Adaptability", "Curiosity", "Data annotation", "Robotics", "AI model training", "AI/machine learning support", "Robotics operations", "Annotation standards", "Quality standards", "KPI definition", "Artificial intelligence", "Human-AI collaboration", "Autonomous systems", "Manipulation robotics", "Mobile robotic systems", "CVAT", "Labelbox", "SageMaker Ground Truth" ], "skillCount" : 25, "jobCategory" : "operations", "dataQualityScore" : 0.8888889, "daysOld" : 2, "hasLocation" : true, "hasGeo" : false }, { "id" : "6a3058bdf292fd229cf43fae", "title" : "Data Entry Specialist", "company" : "Sourcefit", "salary" : { "min" : 315000.0, "max" : 455000.0, "currency" : "PHP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an Entry-level Data Entry Specialist in Quezon City, Philippines, adjusted for full-time onsite employment." }, "location" : "Eastwood Quezon City, PH", "locations" : [ "Eastwood Quezon City", "PH" ], "timestamp" : "2026-06-16T07:03:31.287", "fingerprint" : "76842696737a334f61684186c3848e3feec5e25c14b8782fca4e62aabe394876", "source" : "breezyhr", "language" : "en", "applyUrl" : "https://sourcefit.breezy.hr/p/76a78952e7fa-data-entry-specialist", "externalId" : "76a78952e7fa", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Quezon City", "country" : "Philippines", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "14.6510546,121.0486254" } ], "locationText" : "Quezon City, Philippines", "employmentType" : "FULL_TIME", "coreResponsibilities" : "Enter data into systems, Verify data accuracy, Maintain data integrity, Generate reports from data, Process information accurately", "workSiteFlexibility" : "Onsite", "summaryDescription" : "Data Entry Specialist at Sourcefit. Enter data into systems. Verify data accuracy", "createdAt" : "2026-06-15T22:12:30.356", "lastUpdated" : "2026-06-16T07:03:31.287", "ingestTimestamp" : "2026-06-15T22:12:30.356", "mongoId" : "6a3058bdf292fd229cf43fae", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "operations", "jobSubcategory" : "general", "seniorityLevel" : "Entry", "dataQualityScore" : 0.5555556, "hasLocation" : true, "hasGeo" : true, "llmIndustryConfidence" : 0.85 }, { "id" : "68b706987fc9a711f0f6fdfa", "title" : "Vendor Consultant, Arabic", "company" : "ADCI - Karnataka", "industry" : "Sales, Advertising, Account Management, Retail", "salary" : { "min" : 1500000.0, "max" : 2500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Vendor Consultant in E-commerce in Bengaluru, India, adjusted for company size and industry." }, "location" : "Bengaluru, Karnataka, IND", "locations" : [ "Bengaluru, Karnataka, IND" ], "timestamp" : "2026-06-15T02:44:47.189", "fingerprint" : "1118961c12ca71034544dcd3026a20c91a43b386e5ea7f2895e077fc8984857c", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3052742/apply", "externalId" : "d5881155-2b93-4267-9267-1971c8e58c26", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bengaluru", "state" : "Karnataka", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "12.9767936,77.5900820" } ], "locationText" : "Bengaluru, Karnataka, India", "employmentType" : "FULL_TIME", "professionalSkills" : [ "Vendor management", "Account management", "Business development", "Retail buying", "Retail planning", "Retail allocation", "Product management", "Project management", "Marketing", "E-commerce" ], "hardSkillsList" : [ "Data analysis", "Root cause analysis" ], "softSkillsList" : [ "Customer centric", "Creative", "Thought leadership" ], "hardSkills" : [ { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Root cause analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Customer centric" }, { "name" : "Creative" }, { "name" : "Thought leadership" } ], "majorSkills" : "Vendor management, Account management, Sales, Business development", "majorSkillsList" : [ "Vendor management", "Account management", "Sales", "Business development" ], "coreResponsibilities" : "Manage vendor relationships, Champion vendor needs at Amazon, Build communication channels, Set proper expectations, Provide clear status communications, Manage towards a growth plan, Build strategic account plan, Execute strategic account plan, Deliver on business opportunities, Deliver on relevant KPIs, Improve operational aspects, Provide great consumer experience, Conduct deep dive analysis, Publish recommendations, Publish action plans, Improve vendor experience, Provide thought leadership, Plan roadmaps, Execute roadmaps, Establish long term partnerships, Support new program launches, Support new category launches, Support new feature launches, Conduct regular WBRs, Conduct regular MBRs, Highlight business metric performance, Build action plans", "teamCollaboration" : "Internal teams; Retail teams; Vendor Services teams; Retail Category Team; Internal Amazon teams", "projectManagementSkills" : [ "Roadmap planning" ], "domainKnowledge" : "E-commerce; Retail buying; Retail planning; Retail allocation", "domainList" : [ "e-commerce", "retail-buying", "retail-planning", "retail-allocation" ], "domainSpecificKnowledge" : [ "E-commerce", "Retail buying", "Retail planning", "Retail allocation" ], "communicationSkills" : "Written communication; Oral communication; Presentation skills; Active listening; Consultative communication; Solutions-oriented communication", "problemSolvingSkills" : "Root cause analysis; Develop original ideas; Develop solutions", "outcomesObjectives" : "Grow vendor traffic; Grow brand awareness; Grow customer conversion; Grow revenue; Improve vendor performance; Create great customer experience", "qualificationsBasic" : "5+ years relevant experience, Proficiency in Arabic, Vendor management experience, Sales experience, Post sales experience, Account management experience, Business development experience, B2B business management experience, Analytical skills, Excellent written communication skills, Excellent oral communication skills, Excellent presentation skills, Active listening skills, Consultative skills, Solutions-oriented skills, Ability to work in teams, Ability to deliver results, High standards of work", "qualificationsPreferred" : "E-commerce experience, Retail buying experience, Retail planning experience, Retail allocation experience, Product management experience, Project management experience, Marketing experience, E-commerce experience, Lean Six Sigma experience, MBA/PGDM qualification", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "About Amazon.com Amazon.com strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. By giving customers more of what they want - low prices, vast selection, and convenience - Amazon.com continues to grow and evolve as a world-class e-commerce platform. Amazon's evolution from Web site to e-commerce partner to development platform is driven by the spirit of innovation that is part of the company's DNA. The world's brightest technology minds come to Amazon.com to research and develop technology that improves the lives of shoppers and sellers around the world. About the Role Account Management- Vendor Consultant As a Vendor Consultant as part of Paid Selling Partner Services (PSPS) Team of Retail Business Services, you will have the exciting opportunity to help shape and deliver on a strategy for managing Amazon Vendors. PSPS team is looking for a bright, customer centric, driven, and creative candidate to join our team. You will interface internally with leaders from our Retail and Vendor Services teams and will be responsible for all aspects of the vendor’s business with Amazon. You will engage directly with multiple internal teams to optimize the product line for key manufacturers (vendors) on Amazon.com. You will utilize a wide range of skills and work across major functional areas such as site merchandising, buying, Catalog management, inventory management, finance, operations, and online marketing, to drive the performance of strategic vendor partners at Amazon. In this role you will be focused on the strategic and operational aspects of managing the customer relationships with our vendors. You will conceive, create, and analyze a wide range of marketing and site merchandising efforts, to include marketing campaigns to grow the vendor’s traffic, brand awareness, customer conversion, and revenue on Amazon. Also you will look into strategic and operational aspects of their business with Amazon, root cause analysis of issues and opportunities affecting the vendor’s business. In addition, you are expected to proactively identify areas for growing Vendor’s business by developing strategies. Responsibilities Include · Success will be measured by the performance of your internal teams on input metrics and impact of vendors on creating a great customer experience for buying consumers · Partnering with the Retail Category Team and managing the vendor relationship by championing the vendor’s needs at Amazon · Build communication channels at all levels, set proper expectations, provide clear status communications, and manage towards a growth plan for the vendors · Build and execute on a strategic account plan that delivers on key business opportunities and relevant KPIs for the vendors and Amazon · Work with internal Amazon teams/vendors to improve operational aspects of their business in providing a great consumer experience · Conduct deep dive analysis on the handled issues for the vendors and publish recommendations and action plans based on data to improve vendor experience · Provide thought leadership around planning, roadmaps and execution · Establish long term partnerships with key vendor partners for the group of vendors handled · Support the launches of new programs, categories and features · Conduct regular WBR, MBRs with the vendors highlight business metric performance and building action plans Basic Qualifications: Basic Qualifications and Skills Required · An understanding of and passion for e-commerce · Language preference - Proficiency in Arabic · Work experience is preferred (5+ years). Relevant experience in Vendor management, Sales, post sales, Account Management, and Business Development in managing B2B Business. · Exposure to retail buying, retail planning & allocation, product/project management, marketing or e-commerce will be a plus · Proven analytical skills and demonstrated ability to manage the business “by the numbers”. · Excellent written and oral communication and presentation skills. Ability to express thoughts logically and succinctly. Demonstrated active listening skills, highly consultative and solutions-oriented · Operate in a fast-moving and sometimes ambiguous environment with full control and responsibility of achieving business objectives · Develop original ideas, approaches, and solutions to typical, unusual or difficult situations or problems · Ability to work in teams and ultimately focus on delivering results with high standards · Attention to detail and capability to work on multiple projects in parallel Preferred Qualifications: · Lean Six Sigma experience. · MBA/PGDM qualification. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.", "summaryDescription" : "Vendor Consultant, Arabic at ADCI - Karnataka. Skills: Vendor management, Account management, Sales, Business development. Manage vendor relationships. Champion vendor needs at Amazon", "postedDate" : "2026-06-13T06:39:48.355", "createdAt" : "2026-06-13T06:39:48.355", "lastUpdated" : "2026-06-15T02:44:47.189", "ingestTimestamp" : "2026-06-13T06:39:48.355", "mongoId" : "68b706987fc9a711f0f6fdfa", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3052742/apply", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Data analysis", "Root cause analysis", "Customer centric", "Creative", "Thought leadership", "Vendor management", "Account management", "Sales", "Business development", "Retail buying", "Retail planning", "Retail allocation", "Product management", "Project management", "Marketing", "E-commerce", "Roadmap planning" ], "skillCount" : 17, "jobCategory" : "marketing", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a2a697b74d8ee00a06380b1", "title" : "Program Manager - Data Collection & Annotation - India", "company" : "Skild AI", "salary" : { "min" : 2500000.0, "max" : 3500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : false }, "location" : "Bengaluru, Karnataka, India", "locations" : [ "Bengaluru", "Karnataka", "India" ], "timestamp" : "2026-06-13T21:18:13.975", "fingerprint" : "b949f6196ac8ab574005102ec73d90626e9cc34ec6783e4dfd0829cb2b8839c4", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/skildai-careers/jobs/5254601008", "externalId" : "5254601008", "structuredLocations" : [ { "city" : "Bengaluru", "state" : "Karnataka", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "12.9767936,77.5900820" } ], "locationText" : "Bengaluru, Karnataka, India", "experienceLevel" : "Manager", "professionalSkills" : [ "Program management", "Operations management" ], "hardSkillsList" : [ "Data collection", "Data annotation", "Process setup", "Metrics tracking", "Problem-solving" ], "hardSkills" : [ { "name" : "Data collection", "level" : "intermediate" }, { "name" : "Data annotation", "level" : "intermediate" }, { "name" : "Process setup", "level" : "intermediate" }, { "name" : "Metrics tracking", "level" : "intermediate" }, { "name" : "Problem-solving", "level" : "intermediate" } ], "majorSkills" : "Program management, Data collection, Data annotation", "majorSkillsList" : [ "Program management", "Data collection", "Data annotation" ], "coreResponsibilities" : "Drive program management for data collection, Drive program management for annotation workflows, Coordinate cross-functional execution, Coordinate with 3rd part vendors, Coordinate with tooling, Coordinate with annotation teams, Set up scalable operational processes, Set up metrics, Set up execution frameworks, Own timelines, Own quality, Own throughput, Own metrices, Own operational problem-solving", "teamCollaboration" : "Cross-functional execution; Research teams; Engineering teams", "projectManagementSkills" : [ "Program management" ], "domainKnowledge" : "Robotics foundation models; General-purpose robotics", "domainList" : [ "robotics-foundation-models", "general-purpose-robotics" ], "domainSpecificKnowledge" : [ "Robotics foundation models", "General-purpose robotics" ], "innovationCreativity" : "Innovative projects", "problemSolvingSkills" : "Operational problem-solving", "qualificationsBasic" : "2–3 years program management experience, 2–3 years operations experience", "qualificationsPreferred" : "Startup experience, High-growth environment experience, Execution skills, Communication skills, Stakeholder management skills, Background from top-tier engineering institutions, Background from MBA institutions, High ownership mindset, Ability to operate in ambiguity, Ability to scale complex operations", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Company Overview At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects. Postion Overview We're looking for a high-agency Program Manager to build and scale data collection and annotation pipelines that power our robotics foundation models. In this role, you'll own end-to-end operations across vendor coordination, data quality, and annotation workflows — working cross-functionally with research and engineering teams to ensure we have the high-quality training data needed to advance the frontier of general-purpose robotics. Responsibilities Drive end-to-end program management for egocentric/UMI/teleops data collection and annotation workflows Coordinate cross-functional execution across operations, 3rd part vendors, tooling, vendors, and annotation teams Set up scalable operational processes, metrics, and execution frameworks in fast-paced startup environments Own timelines, quality, throughput, metrices and operational problem-solving across multiple programs Preferred Qualifications 2–3 years of program management / operations experience in startups or high-growth environments Strong execution, communication, and stakeholder management skills Background from top-tier engineering and MBA institutions in India High ownership mindset with ability to operate in ambiguity and scale complex operations Base Salary Range ₹25—₹35 INR", "summaryDescription" : "Program Manager - Data Collection & Annotation - India at Skild AI. Skills: Program management, Data collection, Data annotation. Drive program management for data collection. Drive program management for annotation workflows", "postedDate" : "2026-06-11T20:46:07.734", "createdAt" : "2026-06-11T20:46:07.734", "lastUpdated" : "2026-06-13T21:18:13.975", "ingestTimestamp" : "2026-06-11T20:46:07.734", "mongoId" : "6a2a697b74d8ee00a06380b1", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Data collection", "Data annotation", "Process setup", "Metrics tracking", "Problem-solving", "Program management", "Operations management", "Robotics foundation models", "General-purpose robotics" ], "skillCount" : 9, "jobCategory" : "operations", "jobSubcategory" : "operations", "dataQualityScore" : 0.8888889, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a2c903574d8ee00a097f879", "title" : "Arabic Speaking Behavior Technician", "company" : "Centria Autism", "industry" : "Healthcare", "salary" : { "min" : 16.0, "max" : 20.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Garden City, Michigan, United States", "locations" : [ "Garden City", "Michigan", "United States" ], "certifications" : [ "CPR Certification", "First Aid Certification" ], "timestamp" : "2026-06-15T07:13:21.796", "fingerprint" : "67e645237954ff41491f593c95f0a477e8eae482ae15ff9c2b276e61b1c9854c", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/centriaautism/jobs/8585633002", "externalId" : "8585633002", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Garden City", "state" : "Michigan", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "42.3255929,-83.3310422" } ], "locationText" : "Garden City, Michigan, United States", "minimumEducation" : "High school diploma or GED", "professionalSkills" : [ "Behavior intervention plans", "Evidence-based techniques", "Teaching skills", "Reducing behaviors" ], "hardSkillsList" : [ "Behavioral analysis" ], "softSkillsList" : [ "Patient", "Compassionate" ], "hardSkills" : [ { "name" : "Behavioral analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Patient" }, { "name" : "Compassionate" } ], "majorSkills" : "Behavior Technician, Autism intervention", "majorSkillsList" : [ "Behavior Technician", "Autism intervention" ], "coreResponsibilities" : "Work one-on-one with children, Implement behavior intervention plans, Teach communication skills, Teach social skills, Teach daily living skills, Reduce interfering behaviors", "teamCollaboration" : "Work well in team", "domainKnowledge" : "Autism; Behavioral analysis", "domainList" : [ "autism", "behavioral-analysis" ], "domainSpecificKnowledge" : [ "Autism", "Behavioral analysis" ], "continuousLearning" : "Comprehensive training", "specialRequirements" : "Standing, Walking, Sitting, Grasping, Reaching, Bending, Kneeling, Crouching, Squatting, Lifting, Carrying children, Carrying objects, Lift up to 50 pounds", "outcomesObjectives" : "Make a real difference; Help children reach potential; Made a meaningful impact", "qualificationsBasic" : "18+ years of age, Ability to obtain CPR, Ability to obtain First Aid Certification, Ability to obtain Tuberculosis test, Ability to pass background check, Ability to move in various positions, Ability to lift and carry up to 50 pounds", "qualificationsPreferred" : "Experience with children with autism, Board Certified Behavior Analyst guidance", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "We are looking for enthusiastic individuals to join our team as Behavior Technicians. As a Behavior Technician, you will have the opportunity to make a real difference in the lives of children with autism. In this role, you will work one-on-one with children, implementing individualized behavior intervention plans under the guidance of a Board Certified Behavior Analyst (BCBA). You will use evidence-based techniques to teach communication, social, and daily living skills while reducing interfering behaviors. We are looking for candidates who are passionate about helping children with autism reach their full potential. You will need to be patient, compassionate, and able to work well in a team environment. We will provide comprehensive training so that you are equipped and empowered to help each child, even if you don’t currently have experience. Children can be unpredictable and potentially confrontational, so this role is not for the weak of spirit, mind, or body. Part of the joy of working with kids is exercise! Our clients move, so you need to be comfortable standing, walking, sitting, grasping, reaching, bending, kneeling, crouching, squatting, lifting, and at times carrying children or objects that weigh up to 50 pounds. At the end of each day, you will go home knowing that you have made a meaningful impact on the life of a child and their family. Join us and become a part of a dedicated team that is changing lives for the better. Apply now to start your journey as a Behavior Technician with us! Pay Range: $16 - $20 Requirements: Passionate about helping children with autism Patient, compassionate, and able to work well in a team 18+ years of age High school diploma or GED Ability to obtain a CPR, First Aid Certification and Tuberculosis test (if you haven’t had one in the last year) Ability to pass a pre employment background check Ability to move in various positions (sit, squat, bend, etc.) Ability to lift and carry up to 50 pounds Perks of Working at Centria: Structured career path in the field of Behavioral Analysis Discounts to hundreds of retail partners via our Benefit Hub Access to Centria’s Employee Assistance Plan with benefits around mental health and counseling Early wage access to employees through Rain - Work today, get paid tomorrow! Unlimited opportunities to make an impact in the life of a special needs child We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, Veteran status, or disability status. This job description is not intended to be an exhaustive list of qualifications, skills, efforts, duties, responsibilities, or working conditions associated with the position. This pay scale range is the full range of potential wages Centria Autism reasonably expects to pay for employees with this job title and this pay scale range varies dependent on job qualifications, performance, experience, and/or seniority. This range should not be interrupted to mean that Centria Autism currently employs any employees with this job title at the bottom or top of the pay scale range. Centria reserves the right to amend this job description at any time, with or without written notice.", "summaryDescription" : "Arabic Speaking Behavior Technician at Centria Autism. Skills: Behavior Technician, Autism intervention. Work one-on-one with children. Implement behavior intervention plans", "postedDate" : "2026-06-13T22:01:28.724", "createdAt" : "2026-06-13T22:01:28.724", "lastUpdated" : "2026-06-15T07:13:21.796", "ingestTimestamp" : "2026-06-13T22:01:28.724", "mongoId" : "6a2c903574d8ee00a097f879", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 33280, "salaryAnnualMax" : 41600, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Behavioral analysis", "Patient", "Compassionate", "Behavior Technician", "Autism intervention", "Behavior intervention plans", "Evidence-based techniques", "Teaching skills", "Reducing behaviors", "Autism", "CPR Certification", "First Aid Certification" ], "skillCount" : 12, "jobCategory" : "healthcare", "jobSubcategory" : "support", "seniorityLevel" : "Entry", "dataQualityScore" : 0.7777778, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.98 }, { "id" : "6a30519bf292fd229cf0320a", "title" : "Financial Data Application Specialist", "company" : "AlphaSense", "industry" : "SaaS", "salary" : { "min" : 110000.0, "max" : 150000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Financial Data Application Specialist in the US SaaS industry, adjusted for company size and remote work." }, "location" : "Remote - United States", "locations" : [ "Remote - United States" ], "timestamp" : "2026-06-16T08:22:27.217", "fingerprint" : "72716064eef54cded556ee70f4b8b3fb77c76aa7573f8d9d04aecaecd04b37e5", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/alphasense/jobs/8584930002", "externalId" : "8584930002", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "technicalSkills" : "AI", "professionalSkills" : [ "Financial data analysis", "Quantitative analysis", "Valuation decisions", "Sales enablement", "Product marketing", "Support articles" ], "hardSkillsList" : [ "Financial modeling" ], "softSkillsList" : [ "Entrepreneurial minded", "Teaching", "Enablement" ], "hardSkills" : [ { "name" : "Financial modeling", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Entrepreneurial minded" }, { "name" : "Teaching" }, { "name" : "Enablement" } ], "majorSkills" : "Financial data, Sales, Customer success, Technical implementation", "majorSkillsList" : [ "Financial data", "Sales", "Customer success", "Technical implementation" ], "coreResponsibilities" : "Assist sales in demos, Assist sales in strategic trials, Run trial training calls, Overcome common objections, Communicate value proposition, Speak with users, Visit users, Provide advanced training, Provide customizations, Provide product consultations, Build custom templates, Build bespoke modeling tools, Package use cases for sales, Package use cases for account management, Create how-to videos, Create enablement materials, Create support articles, Field feedback, Identify product opportunities, Relay product information, Act as escalation point, Resolve challenges, Integrate modeling solutions", "teamCollaboration" : "Partner with sales; Partner with product; Partner with marketing; Partner with leadership; Work with account management", "domainKnowledge" : "Financial data; Investment decisions; Valuation decisions; Capital markets", "domainList" : [ "financial-data", "investment-decisions", "valuation-decisions", "capital-markets" ], "domainSpecificKnowledge" : [ "Financial data", "Investment decisions", "Valuation decisions", "Capital markets" ], "toolProficiency" : [ "Excel Add-ins" ], "communicationSkills" : "Distill complex issues; Explain complex issues", "qualificationsBasic" : "Client-facing professional, Develop rapport with people, Maintain relationships, Speak the language of finance, Analyze company financial data, Benchmark financial data, Understand quantitative tools, Become SME for financial data", "qualificationsPreferred" : "New York City strongly preferred", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "About AlphaSense: The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content. The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Come join us! Location: New York City strongly preferred, Remote considered Reports To: Manager, Financial Data Application Specialists About the Role The Financial Data Application Specialist role at AlphaSense lives at the intersection of sales, customer success, and technical implementation for AlphaSense’s financial data products. This is a new team at AlphaSense supporting a strategic area of investment for the business, so we are looking for entrepreneurial minded people that can use learnings from client discussions to help optimize both our go-to-market and product strategies. Specialists add value across our revenue organization by building relationships with prospects and clients, providing deep technical knowledge to demonstrate the value of AlphaSense’s financial data while helping to drive adoption. Due to the extensive exposure that Specialists have with clients, they’re also in a prime location to partner with our sales, product, marketing and leadership teams in determining future product developments that will resonate with the market. What You’ll Do Growth Initiatives: Assist sales in demos and strategic trials of AlphaSense’s financial data solutions. The team also runs trial training calls, making the ability to overcome common objections and communicate our value proposition essential to success. Customer Health: The team works hand in hand with account management, speaking with and visiting users to provide advanced training, customizations, and product consultations. Specialists often drive adoption by building custom templates or other bespoke modeling tools for our customers. Subject Matter Expert: Specialists have expertise in quantitative analysis for investment and valuation decisions. They know the use cases that our customers are likely to care about, and package it for utilization by sales and account management. This can come in the form of how-to videos, enablement, product marketing, support articles and others that can be used for meetings or email distribution. Product Direction: Because of our Specialists’ deep understanding of both our financial data products and customers, they are in a position to field feedback and identify product opportunities, and relay that information across the organization (account management, account executives, product, management). Consultative Support: Act as an escalation point for our product and support teams on difficult scenarios our customers may face with our solutions, particularly when leveraging Excel Add-ins. Manage and resolve challenges related to the full integration of our modeling solutions into our clients’ workflows. Who You Are A client-facing professional with a superior ability to develop rapport with new people, and to maintain relationships, combined with a positive and proactive personality. Someone who has worked with external stakeholders — whether senior investment professionals, corporate development and M&A teams, investor relations, corporate strategy, or competitive intelligence functions — and wants to spend their time client-facing and actively engaged with them. Someone who can speak the language of finance and knows how to analyze a company’s financial data, benchmark it against its peers, and understand how professionals in these roles use quantitative tools to make decisions. Committed to becoming a SME for financial data across all industries, personas, and verticals. A passion for technology, AI, and the capital markets. Excellent in 360 degree communication and collaboration. Able to distill and explain complex issues in simple terms — this is a teaching and enablement role, helping clients learn to do things with our product rather than doing the work for them. Genuine interest to learn how the different tools we’ve built contribute to our clients’ processes, to help identify when a particular client should be using them, and to identify solutions that solve for a client’s needs. Intrinsically motivated and a self-starter, with the ability to stay energized in repetitive client conversations and contribute to a dynamic and entrepreneurial team culture. Strong time management, organization, and task prioritization skills, with comfort juggling many moving pieces across a fast-moving, high-growth team. An independent problem-solver, making multiple efforts to solve problems on your own before escalating. Comfortable working in ambiguity, and flexible enough to adapt as needed to drive customer happiness, ideally with experience operating in a smaller, high-growth team environment. Familiar with the institutional investor landscape, financial markets, and investment research — or with the corporate finance landscape (corporate development, M&A, FP&A, IR, strategy) and the quantitative tools those teams rely on. Minimum Qualifications A foundation in finance or corporate finance — for example, progress toward a CFA or a bachelor’s degree in Economics/Finance/Accounting, OR equivalent hands-on exposure to financial analysis through a corporate development, M&A, investor relations, corporate strategy, or competitive intelligence function. 2-4 years of relevant experience in equity research, investment management, private equity, accounting, consulting, corporate development/M&A, investor relations, or a comparable client- or stakeholder-facing role, with a strong desire to move toward client-facing positions. Demonstrated ability to work with financial data in some form — for example, building or interpreting a comparable company's analysis, benchmarking a company against its peers, or understanding how you would approach that work. You do not need to have built three-statement models yourself, but you must be able to speak the language of finance and do benchmarking. Strong Excel abilities (nice to have: familiarity with AI powered spreadsheet tools and/or experience leveraging generative AI tools within productivity software). Excellent communication skills, as you must manage relationships with high-profile fund managers, corporate finance leaders, and junior analysts alike. For base compensation, we set standard ranges for all roles based on function and level benchmarked against similar stage growth companies and internal comparables. In order to be compliant with local legislation, as well as to provide greater transparency to candidates, we share salary ranges on all job postings regardless of desired hiring location. Final offer amounts are determined by multiple factors including candidate experience/expertise and may vary from the amounts listed below. You may also be offered a performance-based bonus, equity, and a generous benefits program. Base Compensation Range $100,000—$125,000 USD AlphaSense is an equal-opportunity employer. We are committed to a work environment that supports, inspires, and respects all individuals. All employees share in the responsibility for fulfilling AlphaSense’s commitment to equal employment opportunity. AlphaSense does not discriminate against any employee or applicant on the basis of race, color, sex (including pregnancy), national origin, age, religion, marital status, sexual orientation, gender identity, gender expression, military or veteran status, disability, or any other non-merit factor. This policy applies to every aspect of employment at AlphaSense, including recruitment, hiring, training, advancement, and termination. In addition, it is the policy of AlphaSense to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations, and ordinances where a particular employee works. Recruiting Scams and Fraud We at AlphaSense have been made aware of fraudulent job postings and individuals impersonating AlphaSense recruiters. These scams may involve fake job offers, requests for sensitive personal information, or demands for payment. Please note: AlphaSense never asks candidates to pay for job applications, equipment, or training. All official communications will come from an @alpha-sense.com email address. If you’re unsure about a job posting or recruiter, verify it on our Careers page. If you believe you’ve been targeted by a scam or have any doubts regarding the authenticity of any job listing purportedly from or on behalf of AlphaSense please contact us. Your security and trust matter to us.", "summaryDescription" : "Financial Data Application Specialist at AlphaSense. Skills: Financial data, Sales, Customer success, Technical implementation. Assist sales in demos. Assist sales in strategic trials", "postedDate" : "2026-06-15T23:21:59.739", "createdAt" : "2026-06-15T23:21:59.739", "lastUpdated" : "2026-06-16T08:22:27.217", "ingestTimestamp" : "2026-06-15T23:21:59.739", "mongoId" : "6a30519bf292fd229cf0320a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 110000, "salaryAnnualMax" : 150000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Financial modeling", "Entrepreneurial minded", "Teaching", "Enablement", "Financial data", "Sales", "Customer success", "Technical implementation", "Financial data analysis", "Quantitative analysis", "Valuation decisions", "Sales enablement", "Product marketing", "Support articles", "Investment decisions", "Capital markets", "Excel Add-ins" ], "skillCount" : 17, "jobCategory" : "sales", "jobSubcategory" : "revenue", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "SaaS", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e138", "title" : "AI Annotator", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 9.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T13:48:42.162", "fingerprint" : "44ced7e4f0098aedd1f90bc140a3fd8a5e24d57d48d24993286af11fade426c4", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4232489009", "externalId" : "4232489009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "High School", "technicalSkills" : "AI, LLMs, Machine learning", "professionalSkills" : [ "Data annotation", "Content evaluation", "Data labeling", "Quality assessment", "Data generation", "Data transformation", "Data review", "Data ranking", "Prompt creation", "Content relevance", "Response generation", "Text rewriting", "Summarization", "Transcription", "Translation", "Data gathering", "Data compilation" ], "hardSkillsList" : [ "Language intricacies", "Reasoning skills" ], "hardSkills" : [ { "name" : "Language intricacies", "level" : "intermediate" }, { "name" : "Reasoning skills", "level" : "intermediate" } ], "majorSkills" : "Generative AI, Large language models", "majorSkillsList" : [ "Generative AI", "Large language models" ], "coreResponsibilities" : "Rate AI model performance, Assess AI model behavior, Label content elements, Assign predefined categories, Evaluate content quality, Evaluate content appropriateness, Generate labels for concepts, Create training data, Apply data transformations, Modify images, Generate new text, Alter audio/video signals, Review data, Identify product feature function, Label model outputs, Identify content type, Order items by criteria, Rank items by criteria, Create prompts for AI, Generate responses from AI, Rewrite existing text, Preserve original meaning, Produce concise summaries, Convert audio to text, Convert language to text, Gather data, Compile data", "domainKnowledge" : "Generative AI; Large language models; AI systems", "domainList" : [ "generative-ai", "large-language-models", "ai-systems" ], "domainSpecificKnowledge" : [ "Generative AI", "Large language models", "AI systems" ], "qualificationsBasic" : "High School Diploma or higher, Professional or Expert level proficiency in English", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certs", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Data Annotators to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A High School Diploma or higher is required. Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $9 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.", "summaryDescription" : "AI Annotator at Innodata Inc.. Skills: Generative AI, Large language models. Rate AI model performance. Assess AI model behavior", "postedDate" : "2026-06-14T04:11:29.134", "createdAt" : "2026-06-14T04:11:29.134", "lastUpdated" : "2026-06-15T13:48:42.162", "ingestTimestamp" : "2026-06-14T04:11:29.134", "mongoId" : "6a2c6ace74d8ee00a090e138", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 18720, "salaryBand" : "<30k", "hasSalary" : true, "allSkills" : [ "Language intricacies", "Reasoning skills", "Generative AI", "Large language models", "Data annotation", "Content evaluation", "Data labeling", "Quality assessment", "Data generation", "Data transformation", "Data review", "Data ranking", "Prompt creation", "Content relevance", "Response generation", "Text rewriting", "Summarization", "Transcription", "Translation", "Data gathering", "Data compilation", "AI systems" ], "skillCount" : 22, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a0d82c858b93c861e9652df", "title" : "Customer Care Agent (Arabic Speaker)", "company" : "Independent Food Company", "industry" : "Food & Beverage", "salary" : { "min" : 60000.0, "max" : 90000.0, "currency" : "AED", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an Entry-level Customer Care Agent in Dubai, UAE, adjusted for the Food & Beverage industry." }, "location" : "Dubai, AE", "locations" : [ "Dubai", "AE" ], "timestamp" : "2026-06-15T22:35:02.362", "fingerprint" : "e30eaedb7b95bbce9b018dadcc0ed2cb6a6c7096592031cce44deca5e5d77564", "source" : "breezyhr", "language" : "en", "applyUrl" : "https://independent-food-company.breezy.hr/p/f599300a28be-customer-care-agent-arabic-speaker", "externalId" : "f599300a28be", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Dubai", "country" : "United Arab Emirates", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "25.0742823,55.1885387" } ], "locationText" : "Dubai, United Arab Emirates", "employmentType" : "FULL_TIME", "coreResponsibilities" : "Handle customer communication across channels, Manage calls, Manage emails, Manage social media, Manage Google Chat", "workSiteFlexibility" : "Onsite", "rawDescription" : "Job Title: Care Contact Center Agent Department: Care Department Reports To: Care Department Manager Location: Office-Based Working Hours: Full-Time Job Purpose The Care Contact Center Agent handles customer communication across different channels including calls, emails, social media, Google Chat", "summaryDescription" : "Customer Care Agent (Arabic Speaker) at Independent Food Company. Handle customer communication across channels. Manage calls", "createdAt" : "2026-06-14T19:33:15.043", "lastUpdated" : "2026-06-15T22:35:02.362", "ingestTimestamp" : "2026-06-14T19:33:15.043", "mongoId" : "6a0d82c858b93c861e9652df", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "50k-75k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "sales", "jobSubcategory" : "customer_success", "seniorityLevel" : "Entry", "dataQualityScore" : 0.6666667, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Food & Beverage", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c903574d8ee00a097f87e", "title" : "Arabic Speaking Behavior Technician", "company" : "Centria Autism", "industry" : "Healthcare", "salary" : { "min" : 17.0, "max" : 20.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Hamtramck, Michigan, United States", "locations" : [ "Hamtramck", "Michigan", "United States" ], "certifications" : [ "CPR certification", "First Aid Certification" ], "timestamp" : "2026-06-15T04:46:37.572", "fingerprint" : "a8fc19dd619609944869ed10efd8ceb86d787c2f1d52b782de74cc88ed6fc99d", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/centriaautism/jobs/8585832002", "externalId" : "8585832002", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Hamtramck", "state" : "Michigan", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "42.3928151,-83.0496438" } ], "locationText" : "Hamtramck, Michigan, United States", "minimumEducation" : "High School", "professionalSkills" : [ "Behavior intervention" ], "hardSkillsList" : [ "Behavioral analysis" ], "softSkillsList" : [ "Patient", "Compassionate" ], "hardSkills" : [ { "name" : "Behavioral analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Patient" }, { "name" : "Compassionate" } ], "majorSkills" : "Behavioral Technician, Autism intervention", "majorSkillsList" : [ "Behavioral Technician", "Autism intervention" ], "coreResponsibilities" : "Work one-on-one with children, Implement behavior intervention plans, Use evidence-based techniques, Teach communication skills, Teach social skills, Teach daily living skills, Reduce interfering behaviors", "teamCollaboration" : "Work well in team environment", "domainKnowledge" : "Autism; Behavioral analysis", "domainList" : [ "autism", "behavioral-analysis" ], "domainSpecificKnowledge" : [ "Autism", "Behavioral analysis" ], "continuousLearning" : "Comprehensive training provided", "specialRequirements" : "Lifting up to 50 pounds, Standing, Walking, Sitting, Grasping, Reaching, Bending, Kneeling, Crouching, Squatting, Carrying children, Carrying objects", "outcomesObjectives" : "Make a real difference in lives of children; Help children reach full potential; Make a meaningful impact on child and family", "qualificationsBasic" : "18+ years of age, High school diploma or GED, Ability to obtain CPR, Ability to obtain First Aid Certification, Ability to obtain Tuberculosis test, Ability to pass background check, Ability to move in various positions, Ability to lift and carry up to 50 pounds", "qualificationsPreferred" : "CPR certification, First Aid certification, Tuberculosis test within last year", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "We are looking for enthusiastic individuals to join our team as Behavior Technicians. As a Behavior Technician, you will have the opportunity to make a real difference in the lives of children with autism. In this role, you will work one-on-one with children, implementing individualized behavior intervention plans under the guidance of a Board Certified Behavior Analyst (BCBA). You will use evidence-based techniques to teach communication, social, and daily living skills while reducing interfering behaviors. We are looking for candidates who are passionate about helping children with autism reach their full potential. You will need to be patient, compassionate, and able to work well in a team environment. We will provide comprehensive training so that you are equipped and empowered to help each child, even if you don’t currently have experience. Children can be unpredictable and potentially confrontational, so this role is not for the weak of spirit, mind, or body. Part of the joy of working with kids is exercise! Our clients move, so you need to be comfortable standing, walking, sitting, grasping, reaching, bending, kneeling, crouching, squatting, lifting, and at times carrying children or objects that weigh up to 50 pounds. At the end of each day, you will go home knowing that you have made a meaningful impact on the life of a child and their family. Join us and become a part of a dedicated team that is changing lives for the better. Apply now to start your journey as a Behavior Technician with us! Pay Range: $17 - $20 Requirements: Passionate about helping children with autism Patient, compassionate, and able to work well in a team 18+ years of age High school diploma or GED Ability to obtain a CPR, First Aid Certification and Tuberculosis test (if you haven’t had one in the last year) Ability to pass a pre employment background check Ability to move in various positions (sit, squat, bend, etc.) Ability to lift and carry up to 50 pounds Perks of Working at Centria: Structured career path in the field of Behavioral Analysis Discounts to hundreds of retail partners via our Benefit Hub Access to Centria’s Employee Assistance Plan with benefits around mental health and counseling Early wage access to employees through Rain - Work today, get paid tomorrow! Unlimited opportunities to make an impact in the life of a special needs child We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, Veteran status, or disability status. This job description is not intended to be an exhaustive list of qualifications, skills, efforts, duties, responsibilities, or working conditions associated with the position. This pay scale range is the full range of potential wages Centria Autism reasonably expects to pay for employees with this job title and this pay scale range varies dependent on job qualifications, performance, experience, and/or seniority. This range should not be interrupted to mean that Centria Autism currently employs any employees with this job title at the bottom or top of the pay scale range. Centria reserves the right to amend this job description at any time, with or without written notice.", "summaryDescription" : "Arabic Speaking Behavior Technician at Centria Autism. Skills: Behavioral Technician, Autism intervention. Work one-on-one with children. Implement behavior intervention plans", "postedDate" : "2026-06-13T20:31:07.879", "createdAt" : "2026-06-13T20:31:07.879", "lastUpdated" : "2026-06-15T04:46:37.572", "ingestTimestamp" : "2026-06-13T20:31:07.879", "mongoId" : "6a2c903574d8ee00a097f87e", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 35360, "salaryAnnualMax" : 41600, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Behavioral analysis", "Patient", "Compassionate", "Behavioral Technician", "Autism intervention", "Behavior intervention", "Autism", "CPR certification", "First Aid Certification" ], "skillCount" : 9, "jobCategory" : "healthcare", "jobSubcategory" : "support", "seniorityLevel" : "Entry", "dataQualityScore" : 0.7777778, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2ac48f74d8ee00a06fe662", "title" : "Language Support Specialist", "company" : "Georgetown University in Qatar", "salary" : { "min" : 110000.0, "max" : 160000.0, "currency" : "QAR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Education industry in Doha, Qatar, adjusted for mid-seniority and part-time employment." }, "location" : "Qatar", "locations" : [ "Qatar" ], "timestamp" : "2026-06-14T20:34:45.300", "fingerprint" : "23bb770bc197d45ddddba56251467c72c5cc5a59599fd437600087faaf5f0375", "source" : "workday", "language" : "en", "applyUrl" : "https://georgetown.wd1.myworkdayjobs.com/Georgetown_Qatar_Careers/job/Qatar/Language-Support-Specialist_JR26057", "externalId" : "JR26057", "locationPoint" : "25.3548,51.1839", "structuredLocations" : [ { "city" : "Doha", "country" : "Qatar", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "25.3108807,51.5081812" } ], "locationText" : "Doha, Qatar", "employmentType" : "PART_TIME", "technicalSkills" : "MS Office, Google Suite, LMS platforms", "professionalSkills" : [ "Language acquisition", "Writing pedagogy", "Language support" ], "hardSkillsList" : [ "Arabic language teaching", "French language teaching", "Tutoring fundamentals", "Language proficiency", "Academic language skills", "Oral proficiency practice", "Writing proficiency practice" ], "softSkillsList" : [ "Independent work", "Collaborative work" ], "hardSkills" : [ { "name" : "Arabic language teaching", "level" : "intermediate" }, { "name" : "French language teaching", "level" : "intermediate" }, { "name" : "Tutoring fundamentals", "level" : "intermediate" }, { "name" : "Language proficiency", "level" : "intermediate" }, { "name" : "Academic language skills", "level" : "intermediate" }, { "name" : "Oral proficiency practice", "level" : "intermediate" }, { "name" : "Writing proficiency practice", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Independent work" }, { "name" : "Collaborative work" } ], "majorSkills" : "Language tutoring, Language program support, Student language tutors", "majorSkillsList" : [ "Language tutoring", "Language program support", "Student language tutors" ], "coreResponsibilities" : "Support language learners, Mentor student tutors, Train student tutors, Assist in workshop design, Assist in workshop delivery, Promote engaged student learning, Promote multilingualism, Promote language proficiency, Provide one-on-one tutoring, Focus on speaking skills, Focus on writing skills, Focus on academic language skills, Provide general support, Provide admin support, Assist students in language development, Practice oral proficiency, Practice writing proficiency, Hold office hours, Facilitate presentations, Facilitate mini-seminars, Facilitate workshops, Bolster language learning acquisition, Create language support resources, Curate language support resources, Deliver training to peer tutors, Provide feedback to peer tutors, Support Arabic peer tutoring, Support language initiatives, Create support materials, Assist with administrative tasks, Assist with special projects, Assist with strategic planning, Prepare presentations, Prepare data review materials, Manage scheduling, Manage planning, Manage event execution, Coordinate with stakeholders, Publicize programming, Recruit participants, Build learning networks, Manage documentation, Organize documentation, Maintain accuracy, Maintain version control, Maintain data confidentiality", "teamCollaboration" : "Multicultural setting", "projectManagementSkills" : [ "Strategic planning" ], "domainKnowledge" : "Language acquisition; Writing pedagogy; Modern Standard Arabic", "domainList" : [ "language-acquisition", "writing-pedagogy", "modern-standard-arabic" ], "domainSpecificKnowledge" : [ "Language acquisition", "Writing pedagogy", "Modern Standard Arabic" ], "toolProficiency" : [ "Google Suite", "MS Office", "LMS platforms" ], "communicationSkills" : "Professional communication", "documentationSkills" : "Documentation management", "specialRequirements" : "Locally based candidates only, Must have sponsorship", "qualificationsBasic" : "Bachelor's degree, 2+ years teaching experience, 2+ years language center experience, Experience with diverse students, Experience with diverse writers", "qualificationsPreferred" : "Master's Degree in related field", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Georgetown University in Qatar (GU-Q) is dedicated to fulfilling Georgetown University’s mission of promoting intellectual, ethical and spiritual understanding through serious and sustained discourse among people of different faiths, cultures, and beliefs. Embodying this spirit of the University, Georgetown’s Qatar campus undertakes education, research, and service in order to advance knowledge and provide students and the community with a holistic educational experience that produces global citizens committed to the service of humankind. We demonstrate the values of Georgetown University; seek to build upon the world-class reputation of the Edmund A. Walsh School of Foreign Service; and work with our partner, Qatar Foundation, in its endeavors to achieve the Qatar National Vision 2030. **Requirements** The Language Support Specialist is a hybrid role designed to support the academic development of the student body at Georgetown University in Qatar. This position combines the academic support responsibilities of a Language Specialist with the administrative and pedagogical oversight of Language Peer Tutors (Arabic and French) as well as general program support for the unit. The incumbent will work within the Office of Academic Services (OAS) to facilitate language learning, provide expert tutoring, and assist in the strategic delivery of language-related programming. **This is a term position (August–May) with a part-time schedule of 29 hours per week. As it is based in Doha, Qatar and offers no relocation assistance, GU-Q is looking for locally based candidates only. This is a non-sponsored position that requires all applicants to already have the necessary sponsorship to live and work in Qatar.** **Key Accountabilities:** * Support Language learners across beginning, intermediate, and advanced levels. * Mentor and train student language tutors (Arabic and French) on the fundamentals of tutoring and language support practices. * Assist in the design and delivery of workshops, seminars, and materials that promote engaged student learning, multilingualism and language proficiency. * Provide expert one-on-one tutoring sessions focusing on speaking, writing, and academic language skills. * Provide general and admin support for OAS programs. **Key Activities:** * Assist students in their Arabic and French language development (writing and oral proficiency practice) * Hold standard office hours for one-on-one sessions focusing on speaking and writing exercises. * Facilitate targeted presentations, strategic mini-seminars, and interactive workshops on behalf of the center to bolster language learning acquisition on campus. * Create and curate language support resources, including high-utility reference handouts, instructional videos, and interactive learning presentations. * Deliver training and provide ongoing feedback to peer tutors for Arabic and French. * Support the Arabic peer tutoring program and other language support initiatives within OAS. * Assist in creating support materials such as handouts, videos, and presentations for use in language tutoring. * Assist with regular administrative tasks, special projects, and strategic planning for student success. * Prepare professional, visually compelling presentations and data review materials for internal and steering committee meetings. * Manage the precise scheduling, continuous planning, and field execution of structural departmental events, including special guest visits and collaborative academic initiatives. * Coordinate with internal and external community stakeholders to publicize OAS programming, recruit participants, and build a cohesive network of learning practice. * Manage and organize program-related physical and digital documentation, maintaining stringent accuracy, version control, and data confidentiality. **Knowledge and Skills:** * Strong understanding of language acquisition and writing pedagogy. * Effective professional communication skills in English, French and Arabic to interact with the campus community. * Demonstrated ability to work both independently and collaboratively in a multicultural setting. * Competency with Google Suite, MS Office, and LMS platforms. * Interest and ability to master other technologies used in the language programs. **Qualifications:** * Bachelor’s degree. * Master’s Degree (completed or in progress) in Arabic Language and Literature, Arabic Applied Linguistics, French, TESOL, Education, or a related field. **Experience:** * 2+ years of relevant experience teaching university-level Modern Standard Arabic or working in a language/writing center at a postsecondary institution. * Proven experience working with culturally and linguistically diverse students and writers. **Current Georgetown Employees:** If you currently work at Georgetown University, please exit this website and login to GMS ([gms.georgetown.edu](http://gms.georgetown.edu/)) using your Net ID and password. Then select the Career worklet on your GMS Home dashboard to view Jobs at Georgetown. **Submission Guidelines:** Please note that in order to be considered an applicant for any position at Georgetown University in Qatar, you must submit a resume/CV for each position of interest. Documents are not kept on file for future positions. Need Assistance: Need some assistance with the application process? Contact us at [guqhr@georgetown.edu](mailto:guqhr@georgetown.edu). EEO Statement: GU is an [_Equal Opportunity Employer_](https://policymanual.hr.georgetown.edu/200-hiring-and-employment/201-equal-employment-opportunity-affirmative-action/). All qualified applicants are encouraged to apply, and will receive consideration for employment without regard to age, citizenship, color, disability, family responsibilities, gender identity and expression, genetic information, marital status, matriculation, national origin, race, religion, personal appearance, political affiliation, sex, sexual orientation, veteran status, or any other characteristic [_protected by law_](https://georgetown.box.com/s/jkc3kxwrf56e1n2km0jh1vj09fvanw70) _._ Benefits: Georgetown University offers a wide variety of comprehensive and competitive benefits. Benefits packages include comprehensive health, dental and vision plans, disability and life insurance coverage, retirement savings programs, tuition assistance, voluntary insurance options (including group legal, accident, and critical illness), and much more. Whatever your need, the Office of Faculty and Staff Benefits will be standing by to support you. You can learn more about the benefits offered to eligible faculty and staff at [https://benefits.georgetown.edu](https://benefits.georgetown.edu/) or view the [online interactive benefits guide](https://georgetown.s3.amazonaws.com/2022/GU-2022-Active-Benefits-Guide.html) for more information.", "summaryDescription" : "Language Support Specialist at Georgetown University in Qatar. Skills: Language tutoring, Language program support, Student language tutors. Support language learners. Mentor student tutors", "postedDate" : "2026-06-12T01:12:30.445", "createdAt" : "2026-06-12T01:12:30.430", "lastUpdated" : "2026-06-14T20:34:45.300", "ingestTimestamp" : "2026-06-12T01:12:30.430", "mongoId" : "6a2ac48f74d8ee00a06fe662", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://georgetown.wd1.myworkdayjobs.com/Georgetown_Qatar_Careers/job/Qatar/Language-Support-Specialist_JR26057", "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Arabic language teaching", "French language teaching", "Tutoring fundamentals", "Language proficiency", "Academic language skills", "Oral proficiency practice", "Writing proficiency practice", "Independent work", "Collaborative work", "Language tutoring", "Language program support", "Student language tutors", "Language acquisition", "Writing pedagogy", "Language support", "Strategic planning", "Modern Standard Arabic", "Google Suite", "MS Office", "LMS platforms" ], "skillCount" : 20, "jobCategory" : "customer-service", "seniorityLevel" : "mid", "dataQualityScore" : 0.8888889, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a2c6ace74d8ee00a090e140", "title" : "AI Data Specialist", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 45000.0, "max" : 65000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an Entry-level AI Data Specialist in the US Technology industry, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-16T01:01:55.594", "fingerprint" : "abb6d77b7bd53058287022b99fb48a50f312786581d702a638b99a8d484b5f94", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4266745009", "externalId" : "4266745009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "Bachelor's", "majorSkills" : "Generative AI, Large Language Models", "majorSkillsList" : [ "Generative AI", "Large Language Models" ], "coreResponsibilities" : "Rate/assess AI model performance, Label content elements, Assign predefined categories or labels, Evaluate perceived content quality, Generate labels to advance understanding, Create training data by applying transformations, Review data and identify feature functionality, Label model outputs, Order or rank items, Create prompts for AI systems, Evaluate content relevance, Generate responses to prompts, Rewrite existing text, Produce concise summaries, Convert spoken language to text, Convert content from one language to another, Gather and compile data for AI models", "domainKnowledge" : "Generative AI; Large Language Models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large Language Models" ], "qualificationsBasic" : "Bachelor's degree or higher in a humanities specialization, Professional or Expert level proficiency (C1/C2) in English", "qualificationsPreferred" : "Advanced degrees strongly preferred (Master’s or PhD)", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Generative AI Specialist to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A Bachelor’s degree or higher in a humanities specialization is required. Advanced degrees are strongly preferred (Master’s or PhD) Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $15 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.", "summaryDescription" : "AI Data Specialist at Innodata Inc.. Skills: Generative AI, Large Language Models. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T20:05:52.940", "createdAt" : "2026-06-14T20:05:52.940", "lastUpdated" : "2026-06-16T01:01:55.594", "ingestTimestamp" : "2026-06-14T20:05:52.940", "mongoId" : "6a2c6ace74d8ee00a090e140", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 45000, "salaryAnnualMax" : 65000, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Generative AI", "Large Language Models" ], "skillCount" : 2, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a305f40f292fd229cf7a1e7", "title" : "Senior Data Governance Specialist", "company" : "Rituals", "industry" : "Cosmetics", "salary" : { "min" : 65000.0, "max" : 95000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Data Governance Specialist in Amsterdam, Netherlands, adjusted for the retail industry and company size." }, "location" : "Amsterdam, NH, Netherlands", "locations" : [ "Amsterdam", "NH", "Netherlands" ], "timestamp" : "2026-06-16T09:27:17.772", "fingerprint" : "0361b69b0126b6908620b99bc3203863f55169922df89c989ed45072ee64384e", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/Rituals1/744000132218694-senior-data-governance-specialist", "externalId" : "744000132218694", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Amsterdam", "state" : "North Holland", "country" : "Netherlands", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "52.3730796,4.8924534" } ], "locationText" : "Amsterdam, North Holland, Netherlands", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "mid", "professionalSkills" : [ "Data ownership", "Data quality", "Metadata management", "Data classification", "Change management" ], "hardSkillsList" : [ "Data governance framework", "Data governance tooling", "Data definitions", "Governance structures" ], "softSkillsList" : [ "Influence", "Educate stakeholders", "Challenge ideas constructively" ], "hardSkills" : [ { "name" : "Data governance framework", "level" : "intermediate" }, { "name" : "Data governance tooling", "level" : "intermediate" }, { "name" : "Data definitions", "level" : "intermediate" }, { "name" : "Governance structures", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Influence" }, { "name" : "Educate stakeholders" }, { "name" : "Challenge ideas constructively" } ], "majorSkills" : "Data governance, Change management, Stakeholder engagement", "majorSkillsList" : [ "Data governance", "Change management", "Stakeholder engagement" ], "coreResponsibilities" : "Co-develop data governance framework, Validate data governance framework, Co-develop data governance tooling, Validate data governance tooling, Co-develop organisational structure, Validate organisational structure, Ensure governance initiatives are practical, Ensure governance initiatives are business-focused, Ensure governance initiatives are aligned with operational processes, Use knowledge of products to guide decisions, Use knowledge of processes to guide decisions, Use knowledge of systems to guide decisions, Guide decisions around data definitions, Guide decisions around data classifications, Guide decisions around data ownership, Guide decisions around governance structures, Support onboarding of data owners, Support continuous development of data owners, Organise training sessions, Help build data governance community, Provide feedback on governance design, Provide feedback on governance tooling, Act as data governance ambassador, Create engagement from stakeholders, Create buy-in from stakeholders, Collaborate with cross-functional teams, Support end-to-end adoption of data governance practices", "teamCollaboration" : "Cross-functional teams; Central Data Governance Team; Control & Analytics Department; Business departments; Tech & Data Department", "domainKnowledge" : "Data governance practices; Data ownership model; Data quality improvements; Accountability; Transparency; Governance-minded thinking", "domainList" : [ "data-governance-practices", "data-ownership-model", "data-quality-improvements", "accountability", "transparency", "governance-minded-thinking" ], "domainSpecificKnowledge" : [ "Data governance practices", "Data ownership model", "Data quality improvements", "Accountability", "Transparency", "Governance-minded thinking" ], "communicationSkills" : "Influence stakeholders; Educate stakeholders", "continuousLearning" : "Gain knowledge of Rituals’ products; Gain knowledge of Rituals’ services; Gain knowledge of Rituals’ systems; Gain knowledge of Rituals’ internal culture", "problemSolvingSkills" : "Analytical thinking; Critical thinking", "outcomesObjectives" : "Strengthen data ownership model; Support data quality improvements; Contribute to accountability culture; Contribute to transparency culture; Contribute to governance-minded thinking culture; Successful implementation of data governance policies; Successful adoption of data governance policies; Successful implementation of data governance frameworks; Successful adoption of data governance frameworks; Successful implementation of data governance tooling; Successful adoption of data governance tooling; Improve data quality; Reduce risk; Strengthen organisational readiness", "qualificationsBasic" : "HBO/WO degree, At least 5 years of relevant work experience, Experience in data management, Experience in data governance, Experience in change management, Practical knowledge of data governance topics, Communication skills, Collaboration skills, Analytical thinking skills, Critical thinking skills, Stakeholder engagement skills", "qualificationsPreferred" : "Master's degree in Business Administration, Master's degree in Data Science, Master's degree in Information Management, Experience in training, Experience in facilitation, Experience in community building, Familiarity with data management tools, Familiarity with business processes, Knowledge of Rituals’ products, Knowledge of Rituals’ services, Knowledge of Rituals’ systems, Knowledge of Rituals’ internal culture", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "As our Senior Data Governance Specialist, you play a key role in helping Rituals manage data as a strategic asset. You translate business knowledge into practical and effective data governance practices, ensuring governance frameworks, tooling, and ways of working are aligned with real business needs, processes, and systems. In this role, you act as an important bridge between business teams and the central data governance function. You help strengthen the data ownership model, support data quality improvements, and contribute to a culture where accountability, transparency, and governance-minded thinking are embedded across the organisation. You are part of the Control & Analytics Department and the Central Data Governance Team, reporting to the Head of Reporting & BI. You will work closely with colleagues across all business departments and the Tech & Data Department. YOUR ACCOUNTABILITIES As Senior Data Governance Specialist, you will: * co-develop and validate the data governance framework, tooling, and organisational structure together with the Data Governance Implementation Manager * ensure governance initiatives are practical, business-focused, and aligned with operational processes * use your knowledge of products, processes, and systems to guide decisions around data definitions, classifications, ownership, and governance structures * support the onboarding and continuous development of data owners across the organisation * organise training sessions and help build a strong data governance community * provide constructive feedback on governance design and tooling to improve feasibility, usability, and adoption * act as a data governance ambassador, creating engagement and buy-in from stakeholders at all levels * collaborate closely with cross-functional teams to support the end-to-end adoption of data governance practices In this role, your impact is significant. You contribute directly to the successful implementation and adoption of data governance policies, frameworks, and tooling across Rituals. By bringing practical business input into governance strategy and design, you support Rituals’ long-term data ambition while helping improve data quality, reduce risk, and strengthen organisational readiness. ## Qualifications You are a strong connector who understands both business reality and the value of good data governance. You know how to bring people along, challenge ideas constructively, and translate complexity into practical actions. You are comfortable working across functions and levels, and you enjoy building structure, ownership, and long-term impact. You also have: * an HBO/WO (Bachelor/Master) degree, preferably in Business Administration, Data Science, or Information Management * at least 5 years of relevant work experience * experience in data management, data governance, and change management * practical knowledge of data governance topics such as data ownership, data quality, metadata, and classification * strong communication and collaboration skills, with the ability to influence and educate stakeholders at all levels * strong analytical and critical thinking skills, and the confidence to challenge ideas constructively * experience in training, facilitation, and community building * stakeholder engagement skills that help drive cultural and behavioural change * familiarity with data management tools, business processes, and systems; this is a plus * be open to gain strong knowledge of Rituals’ products, services, systems, and internal culture This is an exciting opportunity to play an important role in shaping and embedding data governance across Rituals. You will work in a highly visible position with broad exposure across the business, where your expertise will help connect people, processes, and data in a meaningful way. If you are passionate about strengthening data ownership, improving governance adoption, and building a more data-aware organisation, this role offers the opportunity to make a real and lasting impact. ## Additional Information YOUR PATH TO A NEW CAREER Grow with us! The next steps are: * Apply via our website (please make sure you meet the requirements and tell us why you apply) * Our recruiter will contact you within 10 working days. * An introductory meeting at at our Central Head Office in Amsterdam follows. * You do an online assessment. * You have the second interview at our Central Head Office in Amsterdam. * In the event of a positive outcome, you will receive a proposal with the terms of employment. Any questions? Recruitment is happy to speak to you via [frederik.vanzeggeren@rituals.com](mailto:pieter.deboer@rituals.com). Please note that applications via e-mail are not taken into consideration.", "summaryDescription" : "Senior Data Governance Specialist at Rituals. Skills: Data governance, Change management, Stakeholder engagement. Co-develop data governance framework. Validate data governance framework", "postedDate" : "2026-06-15T14:35:20.000", "createdAt" : "2026-06-16T00:09:38.092", "lastUpdated" : "2026-06-16T09:27:17.772", "ingestTimestamp" : "2026-06-16T00:09:38.092", "mongoId" : "6a305f40f292fd229cf7a1e7", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "50k-75k", "hasSalary" : false, "allSkills" : [ "Data governance framework", "Data governance tooling", "Data definitions", "Governance structures", "Influence", "Educate stakeholders", "Challenge ideas constructively", "Data governance", "Change management", "Stakeholder engagement", "Data ownership", "Data quality", "Metadata management", "Data classification", "Data governance practices", "Data ownership model", "Data quality improvements", "Accountability", "Transparency", "Governance-minded thinking" ], "skillCount" : 20, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Retail", "llmIndustryConfidence" : 0.98 } ], "status" : 200, "message" : "data annotation specialist arabic language najdi hijazi dialect jobs", "metadata" : { "title" : "data annotation specialist arabic language najdi hijazi dialect" }, "pagination" : { "page" : 0, "limit" : 50, "totalCount" : 55679, "totalPages" : 1114, "hasNext" : true, "hasPrevious" : false } }

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