{ "count" : 36061, "data" : [ { "id" : "6a2c690f74d8ee00a0905d44", "title" : "Identity & Access Management Specialist - AI Trainer - Freelance", "company" : "10x Team", "industry" : "Technology & Product", "salary" : { "min" : 90.0, "max" : 158.0, "currency" : "EUR", "frequency" : "Yearly" }, "location" : "Belgium", "locations" : [ "Belgium" ], "timestamp" : "2026-06-16T01:43:36.688", "fingerprint" : "abd637019c092bdae997799ce89ef0f2597407a8f0abd2023058d07f4abfe090", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/10xteam/d83366b0-09ea-451a-8bfa-a7baf930a7cd/application", "externalId" : "d83366b0-09ea-451a-8bfa-a7baf930a7cd", "industryFunction" : { }, "structuredLocations" : [ { "country" : "European Union", "continent" : "eu", "workMode" : "remote" }, { "country" : "United Kingdom", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "European Union; United Kingdom", "employmentType" : "CONTRACT", "professionalSkills" : [ "Identity management", "Access control", "Regulatory compliance", "Risk mitigation" ], "hardSkillsList" : [ "Identity governance", "Access provisioning", "Authentication frameworks", "Access management", "Role-based access control", "Identity lifecycle management" ], "hardSkills" : [ { "name" : "Identity governance", "level" : "intermediate" }, { "name" : "Access provisioning", "level" : "intermediate" }, { "name" : "Authentication frameworks", "level" : "intermediate" }, { "name" : "Access management", "level" : "intermediate" }, { "name" : "Role-based access control", "level" : "intermediate" }, { "name" : "Identity lifecycle management", "level" : "intermediate" } ], "majorSkills" : "AI Training", "majorSkillsList" : [ "AI Training" ], "coreResponsibilities" : "Review AI-generated outputs, Refine AI-generated outputs, Assess AI-driven recommendations, Develop real-world case studies, Create scenario variations, Identify gaps in AI recommendations, Articulate risks in AI recommendations, Provide structured feedback, Influence AI system interpretation", "domainKnowledge" : "Identity management; Access control models; Authentication; Identity governance; Regulatory frameworks; GDPR; SOX; Digital identity", "domainList" : [ "identity-management", "access-control-models", "authentication", "identity-governance", "regulatory-frameworks", "gdpr", "sox", "digital-identity" ], "domainSpecificKnowledge" : [ "Identity management", "Access control models", "Authentication", "Identity governance", "Regulatory frameworks", "GDPR", "SOX", "Digital identity" ], "continuousLearning" : "AI Academy", "problemSolvingSkills" : "Analytical", "qualificationsBasic" : "Experienced IAM consultant, Based in the EU or UK, Available 8–20 hours per week", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Updated: 11 June 2026 Freelance | 8–20 hrs/week | Remote (EU/UK) Are you an experienced Identity & Access Management (IAM) professional passionate about shaping the next generation of artificial intelligence? Join 10x Team as a Freelance IAM Consultant – AI Trainer and leverage your IAM expertise to improve leading-edge AI models, all while benefiting from the flexibility of remote, project-based work. About Us: 10x Team connects top independent professionals with leading AI labs to advance artificial intelligence. We are seeking skilled IAM specialists based in the EU or UK to help train AI systems in identity management, access control, regulatory compliance, and IAM best practices. Key Responsibilities: - Review and refine AI-generated outputs related to identity governance, access provisioning, and authentication frameworks - Assess the accuracy and practicality of AI-driven recommendations on access management, role-based access control, and compliance - Develop real-world case studies and scenarios from your professional experience in IAM - Create scenario variations covering identity lifecycle management, regulatory requirements, and risk mitigation - Identify and articulate gaps or risks in AI recommendations, providing clear, structured feedback - Influence how AI systems interpret IAM best practices and security standards About You: - Experienced IAM consultant with a proven track record in identity and access management - Based in the EU or UK - Deep understanding of access control models, authentication, identity governance, and regulatory frameworks (e.g., GDPR, SOX) - Analytical and detail-oriented, able to deliver actionable, structured feedback - Available 8–20 hours per week and comfortable working remotely and asynchronously Why Join 10x Team? - Flexible, project-based freelance assignments – 100% remote - Help shape how AI systems interpret and support the future of digital identity and access management - Access to ongoing professional development through the 10x Team AI Academy - Supportive community of independent experts, clear assignment briefs, and streamlined onboarding How to Apply: After applying, you’ll receive an email detailing the steps to: - ⁠Complete a short written assessment - Participate in an AI-powered interview Important: Your application is only complete once you finish all steps via the email link. Please note: these AI Lab missions are not traditional job openings with fixed start dates. Project demand is highly dynamic and matching depends on your expertise, availability, and current AI Lab needs. Some experts are matched within days, while others may wait longer for a suitable project. Step into the future of AI-powered identity and access management – apply today! #LI-TT1 ----------------------------------------- NOTE At 10x, there are two types of opportunities: 1. Traditional freelance missions These are regular project-based opportunities where the listed mission is the actual project you may work on. 2. AI Lab roles For AI Lab roles, we scout, review, and approve profiles for access to future project opportunities. The missions listed for AI Lab roles are not traditional job openings. AI Lab work is often highly confidential as this exposes information of what an AI Lab is working on, and project requests are unpredictable. When an AI Lab request comes in, we often need to respond within 24 hours with suitable talent. Matching depends on the specific needs of each AI Lab project and your niche expertise. Once your profile is reviewed and approved, you may be matched to relevant AI Lab projects when suitable opportunities arise. This can happen within hours, but it may also take months, depending on the researchers at the AI labs and their project needs.", "summaryDescription" : "Identity & Access Management Specialist - AI Trainer - Freelance at 10x Team. Skills: AI Training. Review AI-generated outputs. 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Austin:101 E 15th St (320-4001) (320TX-4001)
101 E 15th St
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The Texas Workforce Commission (TWC) is seeking several Associate Reviewing Attorneys (ARA’s) to join the Agency’s Commission Appeals Department, a division of the TWC’s Office of General Counsel. The department's main office is located in Austin, Texas, but ARA’s are eligible to work statewide and are not limited to the Austin geographic area. The selected candidate must have a secure, dedicated workspace with Internet service, ability to maintain a reliable and consistent work schedule and be available for weekly meetings and group collaboration via Microsoft Teams and other applications during regular business hours. Will need to report to Austin, Texas, as needed. TWC is not considering applications from individuals who require sponsorship for an employment visa, including those with H1B visas or those currently on student or postgraduate visas. You must be a Texas resident to work for the Texas Workforce Commission or willing to relocate to Texas. WHO WE ARE: Texas Workforce Commission connects people with careers across the state. While we are based in Austin on the north lawn of the Texas State Capitol, we have offices statewide and many of our positions are suitable for teleworking. We're a Family Friendly Certified Workplace with great work-life balance, competitive salaries, extensive opportunities for training and development, and fantastic benefits. Commission Appeals is a highly specialized, non-traditional legal practice at TWC, providing essential support to TWC’s three Commissioners by listening to and summarizing informal, administrative hearings and making recommendations for case resolution. Our summaries and recommendations in hundreds of cases per month facilitate the administration of Unemployment Benefits, Wage Claims and other programs, as part of TWC’s mission to promote and support the workforce system of Texas. WHO YOU ARE: You have ability to meet strict production deadlines, foster a positive team attitude, demonstrate strong attention to detail with high volume work, and the ability to handle multiple priorities. As an ARA in Commission Appeals, you will join a select team of self-motivated legal professionals who value having an immediate impact on the citizens and businesses of Texas while working in a positive work environment. No litigation skills or experience are required. This is a non-litigation position with no employment connection to our primary customer, the Commission offices. An Associate Reviewing Attorney performs entry-level to routine (journey-level) legal work, listening to approximately 18 to 20 recorded hearings per week, extracting relevant facts from testimony and evidence, and drafting written summaries (not transcripts) and other documentation for consideration by the Commissioners and their staff on a weekly cycle. Recommendations conform to existing law, the Texas Unemployment Compensation Act, Texas Payday law, and Commission precedent. The Agency provides legal resources, with minimal need for outside legal research. Our Attorneys may also conduct informal, telephonic hearings in accordance with agency guidelines. ARA’s work under moderate supervision, with limited latitude for the use of initiative and independent judgment. They excel in working independently, but also routinely share ideas to facilitate rapid problem solving and consistency of recommendation. We foster a collaborative, small-team environment, a positive attitude and high quality and timeliness expectations. Many of our Attorneys have been with the department for many years. WHAT YOU WILL DO: The Associate Reviewing Attorney (Attorney I) performs entry-level to routine (journey-level) legal work. Work involves examining and preparing legal documents in a timely fashion, rendering legal advice and counsel, conducting hearings, and assisting in preparing cases for agency resolution. There is no direct involvement with litigation. Works under moderate supervision, with limited latitude for the use of initiative and independent judgment. YOU WILL BE TRUSTED TO: -Interpret laws and regulations related to programs administered by TWC. -Review legal sufficiency of appeals. -Draft and review legal case summaries and other work product before release to other offices. -Complete work in a timely fashion. -Analyze recorded testimony and documentary evidence developed at lower–level, informal, administrative hearings relating to programs administered by TWC, including Unemployment Insurance (UI) and Payday/Wage Claims. -Summarize relevant facts and make timely recommendations for the resolution of each case. -Ensure that recommendations conform to existing law, including TUCA, Texas Payday law and Commission precedent. -Prepare a decision for each case in conformity to existing law & Commission precedent. -Prepare correspondence related to such cases. -May conduct ordered hearings. -May participate in Rapid Process Improvement (RPI) initiatives. -Perform related work as assigned. YOU ARE A GREAT FIT WITH: -Experience and/or knowledge of Texas Payday law -Experience and/or knowledge of the Texas Unemployment Compensation Act -Prior experience conducting informal, administrative hearings -Experience as a briefing attorney -Experience drafting case digests -Concise writing style -Demonstrated ability to effectively manage time and accomplish multiple, competing tasks under pressure -Ability to adapt rapidly and professionally to unanticipated instructions or requirements -Experience and/or knowledge of legal principals, practices, and proceedings and of laws, regulations and rules related to TWC -Prior experience and/or knowledge of Commission Appeals policies and procedures -Demonstrated ability to efficiently identify and summarize relevant facts, apply logical analysis, and draft legal documents in a timely fashion -Ability to interpret and apply laws, and use legal reference materials -Ability to work in a team environment, multi-task and work well under pressure while meeting department and agency set deadlines -Skill in communicating effectively orally and in writing -Excellent typing skills of 50 words per minute -Meticulous eye for detail -Experience using Microsoft Word -Ability to adapt and willingness to learn -Personal pride in a job well done for the benefit of others. YOU QUALIFY WITH: -Graduation from an accredited law school approved by the American Bar Association and admission to the State Bar of Texas. YOU GAIN: -A Family Friendly Certified Workplace. -Competitive starting salary: $6,048.00-$6,683.04 per month -Defined Retirement Benefit Plan -Optional 401(k) and 457 accounts -Medical Insurance -Paid time off, including time for vacation, sick and family care leave -Additional benefits for active employees can be found at https://www.ers.texas.gov/Active-Employees/Health-Benefits. VETERANS: Use your military skills to qualify for this position or other jobs! Go to www.texasskillstowork.com to translate your military work experience and training courses into civilian job terms, qualifications, and skill sets. Also, you can compare this position to military occupations (MOS) at the Texas State Auditor's Office by pasting this link into your browser: https://hr.sao.texas.gov/Compensation/MilitaryCrosswalk/MOSC_Legal.pdf HOW TO APPLY: To be considered, please complete a State of Texas Application for Employment and apply online at www.workintexas.com or on Taleo ( Job Search ). TWC is not considering applications from individuals who require sponsorship for an employment visa, including those with H1B visas or those currently on student or postgraduate visas. In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification document form upon hire. A position utilizing this classification will be designated as security sensitive according to the Texas Labor Code, Section 301.042. United States-Texas-Austin", "summaryDescription" : "Associate Reviewing Attorney (Statewide) at Texas Workforce Commission. Skills: Legal document review, Case summarization, Legal recommendations. Interpret laws and regulations. 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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 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 $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" : "Generative AI Annotator at Innodata Inc.. Skills: Generative AI, Large Language Models. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T21:26:50.654", "createdAt" : "2026-06-14T21:26:50.654", "lastUpdated" : "2026-06-16T04:13:40.553", "ingestTimestamp" : "2026-06-14T21:26:50.654", "mongoId" : "6a2c6ace74d8ee00a090e167", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 35000, "salaryAnnualMax" : 55000, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Generative AI", "Large Language Models" ], "skillCount" : 2, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 498.34198, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6ace74d8ee00a090e19f", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T22:00:15.895", "fingerprint" : "66c8079353e9fa6c11cac808fedc31271b22782b2d6ae643235505d084a4ddac", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4248726009", "externalId" : "4248726009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "AI, Generative AI, Large language models, Machine learning models", "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Data compilation", "Prompt creation", "Content summarization", "Language translation", "Text generation" ], "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" }, { "name" : "Prompt creation", "level" : "intermediate" }, { "name" : "Content summarization", "level" : "intermediate" }, { "name" : "Language translation", "level" : "intermediate" }, { "name" : "Text generation", "level" : "intermediate" } ], "majorSkills" : "Generative AI, Large language models, Data evaluation, Content labeling", "majorSkillsList" : [ "Generative AI", "Large language models", "Data evaluation", "Content labeling" ], "coreResponsibilities" : "Rate/assess AI model performance, Label content elements, Assign categories or labels, Evaluate content quality/appropriateness, Generate labels for concept understanding, Create training data for ML models, Apply data transformations, Modify images, Generate new text, Alter audio/video signals, Review data, Identify product feature functionality, Label model outputs, Order or rank items, Create prompts for AI systems, Evaluate content relevance, Generate responses from AI systems, Rewrite existing text, Produce concise summaries, Convert spoken language to text, Convert language from one to another, 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 in humanities, Professional or Expert level proficiency (C1/C2) in English", "qualificationsPreferred" : "Advanced degrees (Master’s or PhD) strongly 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, Large language models, Data evaluation, Content labeling. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T21:45:48.645", "createdAt" : "2026-06-14T21:45:48.645", "lastUpdated" : "2026-06-15T22:00:15.895", "ingestTimestamp" : "2026-06-14T21:45:48.645", "mongoId" : "6a2c6ace74d8ee00a090e19f", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Data compilation", "Prompt creation", "Content summarization", "Language translation", "Text generation", "Generative AI", "Large language models", "Data evaluation", "Content labeling", "Artificial Intelligence" ], "skillCount" : 14, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 497.81134, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e199", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-16T05:50:02.697", "fingerprint" : "3113ad5d9bf55a8dc5f52612347b7832b95f678b5da1261a97fc6643d4683686", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4248751009", "externalId" : "4248751009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "AI, Generative AI, LLMs, Machine learning", "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Prompt generation", "Text summarization", "Translation", "Data gathering" ], "hardSkills" : [ { "name" : "Data labeling", "level" : "intermediate" }, { "name" : "Content evaluation", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Prompt generation", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" } ], "majorSkills" : "Generative AI, LLMs, AI model evaluation", "majorSkillsList" : [ "Generative AI", "LLMs", "AI model evaluation" ], "coreResponsibilities" : "Rate/assess AI model performance, Label content elements, Assign categories or labels to items, Evaluate content quality/appropriateness, Generate labels to advance understanding, Create training data for ML models, Apply transformations to original 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 from AI systems, 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" : "Bachelor's degree or higher in a humanities specialization, Professional or Expert level proficiency (C1/C2) in English", "qualificationsPreferred" : "Advanced degrees (Master's or PhD) strongly 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, LLMs, AI model evaluation. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T20:02:38.715", "createdAt" : "2026-06-14T20:02:38.715", "lastUpdated" : "2026-06-16T05:50:02.697", "ingestTimestamp" : "2026-06-14T20:02:38.715", "mongoId" : "6a2c6ace74d8ee00a090e199", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Prompt generation", "Text summarization", "Translation", "Data gathering", "Generative AI", "LLMs", "AI model evaluation", "Large language models" ], "skillCount" : 11, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 495.4203, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e173", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-16T00:19:41.790", "fingerprint" : "8a614eabb9582efc14f0f5b1d4843a5586d6ad9a717c597f7e5002eba021c90b", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4248694009", "externalId" : "4248694009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "AI, Generative AI, Large Language Models, Machine Learning", "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Prompt generation", "Text summarization", "Translation", "Data gathering" ], "hardSkills" : [ { "name" : "Data labeling", "level" : "intermediate" }, { "name" : "Content evaluation", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Prompt generation", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" } ], "majorSkills" : "Generative AI, Large Language Models, AI model evaluation", "majorSkillsList" : [ "Generative AI", "Large Language Models", "AI model evaluation" ], "coreResponsibilities" : "Rate/assess AI model performance, Label content elements, Assign predefined categories or labels, Evaluate content quality/appropriateness, Generate labels to advance understanding, Create training data for ML models, Apply transformations to original 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 from language models, 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" : "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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, Large Language Models, AI model evaluation. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T20:06:28.196", "createdAt" : "2026-06-14T20:06:28.196", "lastUpdated" : "2026-06-16T00:19:41.790", "ingestTimestamp" : "2026-06-14T20:06:28.196", "mongoId" : "6a2c6ace74d8ee00a090e173", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Prompt generation", "Text summarization", "Translation", "Data gathering", "Generative AI", "Large Language Models", "AI model evaluation" ], "skillCount" : 10, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 494.95255, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e18e", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-16T03:53:52.396", "fingerprint" : "007f75d0ed60948e1288e240cac9340d37236646d6bd6994a2ef2377c0185c26", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4266670009", "externalId" : "4266670009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "Python, R, Scala, Spark, Dbt, SQL, Tableau, Power BI, Looker, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, GCP, Azure", "professionalSkills" : [ "Data engineering", "Data science", "Machine learning", "AI development", "Quantitative analysis", "Business intelligence", "Analytics engineering" ], "hardSkillsList" : [ "Statistical analysis", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference", "Model evaluation", "Data labeling", "Data transformation", "Prompt engineering", "Text summarization", "Speech-to-text", "Translation", "Data gathering", "Data compilation" ], "hardSkills" : [ { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" }, { "name" : "Model evaluation", "level" : "intermediate" }, { "name" : "Data labeling", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Prompt engineering", "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" : "Generative AI, Large language models, AI model evaluation, Data annotation", "majorSkillsList" : [ "Generative AI", "Large language models", "AI model evaluation", "Data annotation" ], "coreResponsibilities" : "Rate AI model performance, Label content elements, Assign predefined categories, Evaluate content quality, Generate labels for concepts, Create training data, Apply data transformations, Review data for product features, Label model outputs, Order or rank items, Create prompts for AI systems, Evaluate content relevance, Generate responses from AI systems, Rewrite existing text, Produce concise summaries, Convert audio to text, Translate spoken language, Gather and compile data", "domainKnowledge" : "Generative AI; Large language models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large language models" ], "toolProficiency" : [ "Dbt Cloud" ], "qualificationsBasic" : "Bachelor's degree or higher in humanities, Professional or Expert level proficiency in English", "qualificationsPreferred" : "Advanced degrees (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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, Large language models, AI model evaluation, Data annotation. Rate AI model performance. Label content elements", "postedDate" : "2026-06-14T20:03:43.810", "createdAt" : "2026-06-14T20:03:43.810", "lastUpdated" : "2026-06-16T03:53:52.396", "ingestTimestamp" : "2026-06-14T20:03:43.810", "mongoId" : "6a2c6ace74d8ee00a090e18e", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Statistical analysis", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference", "Model evaluation", "Data labeling", "Data transformation", "Prompt engineering", "Text summarization", "Speech-to-text", "Translation", "Data gathering", "Data compilation", "Generative AI", "Large language models", "AI model evaluation", "Data annotation", "Data engineering", "Data science", "Machine learning", "AI development", "Quantitative analysis", "Business intelligence", "Analytics engineering", "Dbt Cloud" ], "skillCount" : 28, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 494.52017, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e187", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-16T02:27:07.083", "fingerprint" : "450169e15877e435d8fd4791ec2f1f380973f567dd93242ec7bfbc38fe044510", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4266665009", "externalId" : "4266665009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "Python, Generative AI, Large Language Models", "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Prompt generation", "Text summarization", "Language translation", "Data gathering" ], "hardSkills" : [ { "name" : "Data labeling", "level" : "intermediate" }, { "name" : "Content evaluation", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Prompt generation", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Language translation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" } ], "majorSkills" : "Generative AI, Large Language Models, Data labeling", "majorSkillsList" : [ "Generative AI", "Large Language Models", "Data labeling" ], "coreResponsibilities" : "Rate/assess AI model performance, Label content elements, Assign categories or labels, Evaluate content quality/appropriateness, Generate labels for concept understanding, Create training data for ML models, Apply data transformations, Modify images, Generate new text, Alter audio/video signals, Review data for 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 from AI systems, 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" : "Bachelor's degree or higher in humanities, Professional or Expert level proficiency (C1/C2) in English", "qualificationsPreferred" : "Advanced degrees (Master's or PhD) strongly 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, Large Language Models, Data labeling. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T20:07:38.719", "createdAt" : "2026-06-14T20:07:38.719", "lastUpdated" : "2026-06-16T02:27:07.083", "ingestTimestamp" : "2026-06-14T20:07:38.719", "mongoId" : "6a2c6ace74d8ee00a090e187", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Prompt generation", "Text summarization", "Language translation", "Data gathering", "Generative AI", "Large Language Models" ], "skillCount" : 9, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 494.1072, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e19d", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-16T03:08:18.991", "fingerprint" : "4ef79946b63e032c9cbe6abadbc5526b830a5ef329c30c01158af2b3ee18a1fb", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4248748009", "externalId" : "4248748009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "AI, Generative AI, Large language models, Machine learning models", "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Data compilation", "Prompt creation", "Content summarization", "Language translation", "Text conversion" ], "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" }, { "name" : "Prompt creation", "level" : "intermediate" }, { "name" : "Content summarization", "level" : "intermediate" }, { "name" : "Language translation", "level" : "intermediate" }, { "name" : "Text conversion", "level" : "intermediate" } ], "majorSkills" : "Generative AI, Large language models, Data labeling, Content evaluation", "majorSkillsList" : [ "Generative AI", "Large language models", "Data labeling", "Content evaluation" ], "coreResponsibilities" : "Rate/assess AI model performance, Label content elements, Assign predefined categories/labels, Evaluate content quality/appropriateness, Generate labels for concept understanding, Create training data for ML models, Apply data transformations, Review data for product feature functionality, Label model outputs, Order or rank items, Create prompts for AI systems, Evaluate content relevance, Generate responses from AI systems, Rewrite existing text, Produce concise summaries, Convert spoken language to text, Convert language from one to another, 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 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, Large language models, Data labeling, Content evaluation. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T19:57:50.943", "createdAt" : "2026-06-14T19:57:50.943", "lastUpdated" : "2026-06-16T03:08:18.991", "ingestTimestamp" : "2026-06-14T19:57:50.943", "mongoId" : "6a2c6ace74d8ee00a090e19d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Data compilation", "Prompt creation", "Content summarization", "Language translation", "Text conversion", "Generative AI", "Large language models", "Artificial Intelligence" ], "skillCount" : 12, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 493.00262, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e198", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-16T01:22:16.790", "fingerprint" : "29c6fd40c135e2bd12e7aa7b6d635cf3405a6d03f877ce63f3efa303056525c2", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4248754009", "externalId" : "4248754009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "Generative AI, AI, LLMs, Machine learning", "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Prompt creation", "Text summarization", "Language translation", "Data gathering" ], "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" : "Language translation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" } ], "majorSkills" : "Generative AI, LLMs, Data labeling", "majorSkillsList" : [ "Generative AI", "LLMs", "Data labeling" ], "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 for ML models, Apply data transformations, Review data for product feature functionality, Label model outputs, Order or rank items, Create prompts for AI systems, Evaluate content relevance, Generate responses from AI systems, 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" : "Bachelor's degree or higher in humanities, 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, LLMs, Data labeling. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T19:09:08.921", "createdAt" : "2026-06-14T19:09:08.921", "lastUpdated" : "2026-06-16T01:22:16.790", "ingestTimestamp" : "2026-06-14T19:09:08.921", "mongoId" : "6a2c6ace74d8ee00a090e198", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Prompt creation", "Text summarization", "Language translation", "Data gathering", "Generative AI", "LLMs", "Large language models" ], "skillCount" : 10, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 492.1923, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e172", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-16T01:38:19.288", "fingerprint" : "cfa5620690e47ea34d0508a3e4d7585243d9add72d1cf2181d45096def423c99", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4248787009", "externalId" : "4248787009", "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", "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Prompt generation", "Text summarization", "Translation", "Data gathering" ], "hardSkills" : [ { "name" : "Data labeling", "level" : "intermediate" }, { "name" : "Content evaluation", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Prompt generation", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" } ], "majorSkills" : "Generative AI, Large Language Models, Data labeling", "majorSkillsList" : [ "Generative AI", "Large Language Models", "Data labeling" ], "coreResponsibilities" : "Rate AI model performance, Label content elements, Assign predefined categories, Evaluate content quality, Generate labels for concepts, Create training data, Apply transformations to data, Modify images, Generate new text, Alter audio/video signals, Review data, Identify product feature functionality, Label model outputs, Order or rank items, Create prompts for AI systems, Evaluate content relevance, Generate responses from AI systems, Rewrite existing text, Produce concise summaries, Convert spoken language to text, Convert text to another language, Gather and compile data", "domainKnowledge" : "Generative AI; Large Language Models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large Language Models" ], "qualificationsBasic" : "Bachelor's degree in humanities, Professional or Expert level proficiency in English", "qualificationsPreferred" : "Advanced degrees (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 $21 CAD 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, Large Language Models, Data labeling. Rate AI model performance. Label content elements", "postedDate" : "2026-06-14T19:14:31.744", "createdAt" : "2026-06-14T19:14:31.744", "lastUpdated" : "2026-06-16T01:38:19.288", "ingestTimestamp" : "2026-06-14T19:14:31.744", "mongoId" : "6a2c6ace74d8ee00a090e172", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Prompt generation", "Text summarization", "Translation", "Data gathering", "Generative AI", "Large Language Models" ], "skillCount" : 9, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 492.08176, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e186", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-16T07:37:14.598", "fingerprint" : "85002d1299df7129ddac220e3c0dca0e358e7c1fd64afc47b19aca3944f1ddac", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4266651009", "externalId" : "4266651009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "AI, LLMs, Machine learning", "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Prompt creation", "Text summarization", "Translation", "Data gathering" ], "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" } ], "majorSkills" : "Generative AI, Large language models", "majorSkillsList" : [ "Generative AI", "Large language models" ], "coreResponsibilities" : "Rate/assess AI model performance, Label content elements, Assign predefined categories/labels, Evaluate content quality/appropriateness, Generate labels for concept understanding, Create training data for ML models, Review data for product feature functionality, Label model outputs, Order or rank items, Create prompts for AI systems, Evaluate content relevance, Generate responses from AI systems, 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" : "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 a 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, Large language models. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T18:57:16.537", "createdAt" : "2026-06-14T18:57:16.537", "lastUpdated" : "2026-06-16T07:37:14.598", "ingestTimestamp" : "2026-06-14T18:57:16.537", "mongoId" : "6a2c6ace74d8ee00a090e186", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Prompt creation", "Text summarization", "Translation", "Data gathering", "Generative AI", "Large language models" ], "skillCount" : 9, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 491.6621, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e177", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-16T01:24:39.336", "fingerprint" : "4f0467675375a0cfb19a2e84ca56a7464e3061e5ea9c59d4688df723ea1b2881", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4248689009", "externalId" : "4248689009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "AI, LLMs, Machine learning", "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Prompt generation", "Text summarization", "Translation", "Data gathering" ], "hardSkills" : [ { "name" : "Data labeling", "level" : "intermediate" }, { "name" : "Content evaluation", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Prompt generation", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" } ], "majorSkills" : "Generative AI, Large language models", "majorSkillsList" : [ "Generative AI", "Large language models" ], "coreResponsibilities" : "Rate/assess AI model performance, Label content elements, Assign categories or labels to items, Evaluate content quality/appropriateness, Generate labels to advance understanding, Create training data for machine learning models, Apply transformations to original data, Review data and identify product feature functionality, Label model outputs, Order or rank items, Create prompts for AI systems, Evaluate content relevance, Generate responses from AI systems, 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" : "Bachelor's degree or higher in a humanities specialization, Professional or Expert level proficiency (C1/C2) in English", "qualificationsPreferred" : "Advanced degrees (Master's or PhD) strongly 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, Large language models. Rate/assess AI model performance. 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Skills: Data Science, AI, Machine Learning, Data Engineering. Develop and implement data science solutions. 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: { }, "structuredLocations" : [ { "city" : "Toronto", "state" : "Ontario", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "43.6534817,-79.3839347" } ], "locationText" : "Toronto, Ontario, Canada", "employmentType" : "FULL_TIME", "experienceLevel" : "Director", "technicalSkills" : "Python, SQL, Scala, Spark, Dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, S3, Glue, SageMaker, Athena, GCP, Vertex AI, Azure, Synapse, ML Studio, Kubernetes, Terraform, Kafka, Flink, Apache Beam, Lambda, Kinesis, Pub/Sub", "professionalSkills" : [ "Data strategy", "Data modeling", "Business intelligence", "Data governance", "ML systems engineering", "Product intelligence", "AI-powered services", "Data-driven decision-making", "Scalable data engineering", "AI/ML systems", "Cloud-based data architectures", "Real-time analytics", "ML/AI-driven solutions", "Client needs", "Data-as-a-product", "Data assets", "Real-time analytics", "AI-powered automation", "Data-driven insights", "Self-service analytics", "Data pipelines", "Enterprise warehousing", "ML training", "Business reporting", "AI-powered features", "Anomaly detection", "Personalization", "Cost optimization", "MLOps", "CI/CD", "Real-time inference", "Recommendations", "Predictive analytics", "NLP", "Generative AI", "Ethical AI", "AI standards", "BI tools", "Dashboards", "Product analytics", "User behavior", "Feature engagement", "Embedded analytics", "SaaS metrics", "Data privacy", "Data security", "Compliance", "Data lineage", "Metadata management", "MDM", "RBAC", "ABAC", "ReBac", "Data sharing", "Data democratization", "Trusted data", "Documented data", "Team leadership", "Budget management", "Product innovations", "Multi-tenant SaaS", "Customer-facing analytics", "Emerging AI trends", "Responsible AI frameworks" ], "hardSkillsList" : [ "Regression", "Classification", "Clustering", "Time-series", "A/B testing", "Causal inference" ], "softSkillsList" : [ "Leadership" ], "hardSkills" : [ { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" } ], "majorSkills" : "Data Engineering, AI/ML Engineering, Data Strategy, Business Intelligence", "majorSkillsList" : [ "Data Engineering", "AI/ML Engineering", "Data Strategy", "Business Intelligence" ], "coreResponsibilities" : "Define and execute data and AI strategy, Lead cross-functional teams, Establish data-as-a-product principles, Drive innovation in real-time analytics, Partner with Product, Engineering, and Customer Success teams, Design and oversee high-scale, cloud-native data architectures, Implement highly available, fault-tolerant data pipelines, Lead data modeling initiatives, Work with engineering teams to embed AI-powered features, Drive observability, monitoring, and cost optimization, Oversee the development of ML/AI models, Implement MLOps best practices, Lead initiatives in AI-powered recommendations, Ensure bias-free, ethical AI practices, Build and manage BI tools, Develop product analytics frameworks, Implement embedded analytics solutions, Optimize reporting for SaaS metrics, Own data governance frameworks, Define and implement data lineage, Drive role-based access controls, Champion data democratization", "teamCollaboration" : "Cross-functional teams; Product teams; Engineering teams; Customer Success teams", "projectManagementSkills" : [ "Agile" ], "domainKnowledge" : "B2B SaaS; Cloud-native architecture; Multi-tenant SaaS; SaaS metrics; GDPR; SOC 2; PIPEDA; CCPA", "domainList" : [ "b2b-saas", "cloud-native-architecture", "multi-tenant-saas", "saas-metrics", "gdpr", "soc-2", "pipeda", "ccpa" ], "domainSpecificKnowledge" : [ "B2B SaaS", "Cloud-native architecture", "Multi-tenant SaaS", "SaaS metrics", "GDPR", "SOC 2", "PIPEDA", "CCPA" ], "toolProficiency" : [ "Collibra", "Informatica", "Alation", "Immuta", "JIRA" ], "communicationSkills" : "Executive presentations; Technical documentation", "documentationSkills" : "Technical writing; API documentation; Architecture diagrams", "continuousLearning" : "Growth opportunities", "innovationCreativity" : "Innovation", "problemSolvingSkills" : "Root cause analysis; Troubleshooting", "qualificationsBasic" : "10+ years of experience in data engineering, AI/ML, or analytics leadership roles, SQL proficiency, Master's or PhD in", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, Dbt Certified", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "MEET BENEVITY Benevity is the way the world does good, providing companies (and their employees) with technology to take social action on the issues they care about. Through giving, volunteering, grantmaking, employee resource groups and micro-actions, we help most of the Fortune 100 brands build better cultures and use their power for good. We’re also one of the first B Corporations in Canada, meaning we’re as committed to purpose as we are to profits. We have people working all over the world, including Canada, Spain, Switzerland, the United Kingdom, the United States and more! We are seeking a Director of Data and ML/AI Engineering to lead our data and AI technology strategy, architecture, and execution within our B2B SaaS Benevity Impact Platform. This role is pivotal in enabling data-driven decision-making, product intelligence, and AI-powered services and automation across our platform. The ideal candidate will have deep expertise in scalable data engineering, AI/ML systems and services, and cloud-based data architectures, with a track record of building highly available, real-time analytics, and ML/AI-driven solutions for SaaS platforms. This role will oversee data science, data modeling, business intelligence, governance, and ML/AI systems engineering, ensuring alignment with our client and business needs. What you’ll do: Leadership & Data Strategy - Define and execute the data and AI strategy for our SaaS platform, ensuring alignment with business objectives and customer needs. - Lead cross-functional teams across data engineering, AI/ML, BI, and governance to deliver scalable, high-impact solutions. - Establish data-as-a-product principles, ensuring data assets are secure, reusable, and monetizable within our platform. - Drive innovation in real-time analytics, AI-powered automation and intelligence for clients. - Partner with Product, Engineering, and Customer Success teams to enhance data-driven insights, reporting, and self-service analytics. Data Engineering & Platform Architecture - Design and oversee high-scale, cloud-native data architectures that support real-time streaming, data lakes / lakehouses, and enterprise warehousing. - Implement highly available, fault-tolerant data pipelines to process, store, and serve insights across the platform. - Lead data modeling initiatives to optimize data structures for analytics, ML training, and business reporting. - Work with engineering teams to embed AI-powered features into the SaaS platform, enabling smart automation, anomaly detection, and personalization. - Drive observability, monitoring, and cost optimization across our cloud-based data infrastructure. AI/ML Engineering & Data Science - Oversee the development of ML/AI models, ensuring they are scalable, explainable, and deployed effectively in production. - Implement MLOps best practices, including CI/CD for models, versioning, and real-time inference. - Lead initiatives in AI-powered recommendations, predictive analytics, NLP, and generative AI to enhance our product offerings. - Ensure bias-free, ethical AI practices and compliance with industry AI standards and regulations. Business Intelligence & Product Analytics - Build and manage BI tools, dashboards, and self-service analytics to provide real-time insights to clients and internal stakeholders. - Develop product analytics frameworks, tracking user behavior, adoption, and feature engagement. - Implement embedded analytics solutions that allow clients to gain actionable insights from their data. - Optimize reporting for SaaS metrics (MRR, ARR, churn, retention, LTV, NPS) and drive data-informed decision-making. Data Governance & Compliance - Own data governance frameworks, ensuring data privacy, security, and compliance (GDPR, SOC 2, PIPEDA, CCPA, etc.). - Define and implement data lineage, metadata management, and master data management (MDM) best practices. - Drive role-based access controls (RBAC, ABAC or ReBac) and ensure secure, auditable data sharing within our SaaS ecosystem. - Champion data democratization, enabling teams to access trusted, well-documented data. What you’ll bring: - 10+ years of experience in data engineering, AI/ML, or analytics leadership roles, ideally in B2B SaaS or cloud-based platforms - Strong expertise in scalable data architectures, ML/AI systems, and embedded analytics - Proven track record in leading high-performance teams, managing budgets, and delivering data-driven product innovations - Experience with multi-tenant SaaS data governance, compliance (SOC 2, GDPR, etc.), and customer-facing analytics - Familiarity with emerging AI trends, including LLMs, Generative AI, and responsible AI frameworks - Familiarity with SaaS product analytics and AI-powered automation use cases - Master’s or PhD in Computer Science, Data Science, AI/ML, or a related field is preferred Technical Skills & Expertise - Data & AI Stacks (Cloud-Native, SaaS-Optimized) - Data Engineering & Storage: BigQuery, Redshift, Delta Lake, Snowflake, Databricks - AI/ML Frameworks: Azure AI, TensorFlow, PyTorch, Hugging Face, MLflow, Vertex AI - MLOps & Pipelines: Kubeflow, SageMaker, Airflow, Feature Stores, DataRobot - BI & Analytics Tools: Looker, Power BI, Mode Analytics, Amplitude, Mixpanel - Data Governance & Security: Collibra, Informatica, Alation, Immuta - Cloud & DevOps: AWS (S3, Lambda, Kinesis), GCP (BigQuery, Pub/Sub), Kubernetes, Terraform - Programming: Python, SQL, Scala, Java - Streaming & Real-Time Data: Kafka, Flink, Apache Beam DISCOVER YOUR PURPOSE AT WORK We’re not employees, we’re Benevity-ites. From all locations, backgrounds and walks of life, who deserve more … Innovative work. Growth opportunities. Caring co-workers. And a chance to do work that fills us with a sense of purpose. If the idea of working on tech that helps people do good in the world lights you up ... If you want a career where you’re valued for who you are and challenged to see who you can become … It’s time to join Benevity. We’re so excited to meet you. WHERE WE WORK At Benevity, we embrace a flexible hybrid approach to where we work that empowers our people in a way that supports great work, strong relationships, and personal well-being. For those located near one of our offices, while there’s no set requirement for in-office time, we do value the moments when coming together in person helps us build connection and collaboration. Whether it’s for onboarding, project work, or a chance to align and bond as a team, we trust our people to make thoughtful decisions about when showing up in person matters most. JOIN A COMPANY WHERE DEIB ISN’T A BUZZWORD Diversity, equity, inclusion and belonging are part of Benevity’s DNA. You’ll see the impact of our massive investment in DEIB daily — from our well-supported employee resources groups to the exceptional diversity on our leadership and tech teams. We know that diverse backgrounds, experiences, skills and passions are what move our business and our people forward, so we're committed to creating a culture of belonging with equal opportunities for everyone to shine. That starts with a fair and accessible hiring process. If you want to feel seen, heard and celebrated, you belong at Benevity. Candidates with disabilities who may require accommodations throughout the hiring or assessment process are encouraged to reach out to accommodations@benevity.com.", "summaryDescription" : "Director, Data and AI Engineering at Benevity. Skills: Data Engineering, AI/ML Engineering, Data Strategy, Business Intelligence. Define and execute data and AI strategy. 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Technical translator between engineering; Work with partners at OpenAI", "projectManagementSkills" : [ "Roadmap planning" ], "domainKnowledge" : "Car ownership; Car insurance; Car financing; Car maintenance; Car safety; Voice models", "domainList" : [ "car-ownership", "car-insurance", "car-financing", "car-maintenance", "car-safety", "voice-models" ], "domainSpecificKnowledge" : [ "Car ownership", "Car insurance", "Car financing", "Car maintenance", "Car safety", "Voice models" ], "communicationSkills" : "Technical translator", "innovationCreativity" : "Pioneer new model capabilities", "problemSolvingSkills" : "Optimistic problem-solver; Data-driven validation", "outcomesObjectives" : "Automate >70% inbound sales; Automate >70% service requests; Improve answer quality; Improve customer satisfaction; Improve automation rates", "qualificationsBasic" : "4+ years management consulting, 4+ years technical product management, Ability to navigate technical tradeoffs, Lead by example implementing AI standards, Turn complex ideas into scalable products", "qualificationsPreferred" : "Proven interest in modern LLM systems", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "WHY JERRY.AI http://Jerry.ai? - We are building the first super app to manage car ownership—an industry where the experience is stuck in the 90s. - Lead a strategic area leveraging LLMs, agents, and internal APIs to automate a fragmented, $2T market. - Work with partners at OpenAI to integrate Jerry.ai http://Jerry.ai services directly into the ChatGPT App and pioneer new model capabilities. LEAD THE AI REVOLUTION FOR JERRY.AI http://Jerry.ai: At Jerry.ai http://Jerry.ai, we are moving past fragmented, time-consuming processes to create a seamless, automated platform. You will sit at the intersection of product, engineering, and applied AI as you build and scale a sophisticated system that already automates >70% of inbound sales and service requests (over 50k chats per month). Your role will include shaping how modern LLM systems, human-in-the-loop feedback, and computer-use agents redefine an entire industry. HOW YOU WILL MAKE AN IMPACT: - Lead end-to-end development for our AI platform and customer experiences, from initial roadmap to rollout. - Partner with engineers to design prompt strategies, evaluation frameworks, and guardrails—balancing latency, cost, and accuracy. - Serve as the technical translator between engineering and the broader organization, establishing AI best practices and platform standards. - Drive systematic improvement in answer quality, customer satisfaction, and automation rates through rigorous experimentation. - Work with partners at OpenAI to evaluate and deploy the next generation of voice models and workflow automation. WHAT WE’RE LOOKING FOR IN A BUILDER: - Intrinsically Motivated Technologist: You live and breathe AI. You read the release notes when a new model drops and you’ve already built your own custom workflows. - Systems Thinker: You are comfortable diving into technical conversations about API design and system architecture, translating complex concepts for any audience. - Optimistic Problem-Solver: You are a \"how can we\" thinker who seeks constant improvement and thrives on owning high-impact metrics. - Data-Driven with Conviction: You are familiar with SQL and comfortable diving into the data to answer your own questions and validate hypotheses. IDEAL PROFILE: - 4+ years of experience in management consulting or technical product management at a fast-paced startup. - Proven interest in modern LLM systems. - Ability to navigate technical tradeoffs and lead by example when implementing AI platform standards. - A track record of taking complex, strategic ideas and turning them into scalable, production-grade products. While we appreciate your interest and application, only applicants under consideration will be contacted. Jerry.ai is proud to be an Equal Employment Opportunity employer. We prohibit discrimination based on race, religion, color, national origin, sex, pregnancy, reproductive health decisions or related medical conditions, sexual orientation, gender identity, gender expression, age, veteran status, disability, genetic information, or other characteristics protected by applicable local, state or federal laws. Jerry.ai is committed to providing reasonable accommodations for individuals with disabilities in our job application process. If you need assistance or an accommodation due to a disability, please contact us at recruiting@jerry.ai recruiting@getjerry.com The successful candidate’s starting pay will fall within the pay range listed on this job posting, determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Ranges are market-dependent and may be modified in the future. In addition to base salary, the compensation may include opportunities for equity grants. We offer a comprehensive benefits package to regular employees, including health, dental, and vision coverage, paid time off, paid parental leave, 401(K) plan with employer matching, and wellness benefits, among others. Equity opportunities may also be part of your total rewards package. Part-time, contract, or freelance roles may not be eligible for certain benefits. About Jerry.ai Jerry.ai is America’s first and only super app to radically simplify car ownership. We are redefining how people manage owning a car, one of their most expensive and time-consuming assets. Backed by artificial intelligence and machine learning, Jerry.ai simplifies and automates owning and maintaining a car while providing personalized services for all car owners' needs. We spend every day innovating and improving our AI-powered app to provide the best possible experience for our customers. From car insurance and financing to maintenance and safety, Jerry.ai does it all. We are the #1 rated and most downloaded app in our category with a 4.7 star rating in the App Store. We have more than 5 million customers — and we’re just getting started. Jerry.ai was founded in 2017 by serial entrepreneurs and has raised more than $240 million in financing. Join our team and work with passionate, curious and egoless people who love solving real-world problems. Help us build a revolutionary product that’s disrupting a massive market.", "summaryDescription" : "Manager, AI Agents and Platform at Jerry. ai. Skills: AI platform, LLM systems, Workflow automation. Lead end-to-end development for AI platform. 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LEAD THE AI REVOLUTION FOR JERRY.AI http://Jerry.ai: At Jerry.ai http://Jerry.ai, we are moving past fragmented, time-consuming processes to create a seamless, automated platform. You will sit at the intersection of product, engineering, and applied AI as you build and scale a sophisticated system that already automates >70% of inbound sales and service requests (over 50k chats per month). Your role will include shaping how modern LLM systems, human-in-the-loop feedback, and computer-use agents redefine an entire industry. HOW YOU WILL MAKE AN IMPACT: - Lead end-to-end development for our AI platform and customer experiences, from initial roadmap to rollout. - Partner with engineers to design prompt strategies, evaluation frameworks, and guardrails—balancing latency, cost, and accuracy. - Serve as the technical translator between engineering and the broader organization, establishing AI best practices and platform standards. - Drive systematic improvement in answer quality, customer satisfaction, and automation rates through rigorous experimentation. - Work with partners at OpenAI to evaluate and deploy the next generation of voice models and workflow automation. WHAT WE’RE LOOKING FOR IN A BUILDER: - Intrinsically Motivated Technologist: You live and breathe AI. You read the release notes when a new model drops and you’ve already built your own custom workflows. - Systems Thinker: You are comfortable diving into technical conversations about API design and system architecture, translating complex concepts for any audience. - Optimistic Problem-Solver: You are a \"how can we\" thinker who seeks constant improvement and thrives on owning high-impact metrics. - Data-Driven with Conviction: You are familiar with SQL and comfortable diving into the data to answer your own questions and validate hypotheses. IDEAL PROFILE: - 4+ years of experience in management consulting or technical product management at a fast-paced startup. - Proven interest in modern LLM systems. - Ability to navigate technical tradeoffs and lead by example when implementing AI platform standards. - A track record of taking complex, strategic ideas and turning them into scalable, production-grade products. While we appreciate your interest and application, only applicants under consideration will be contacted. Jerry.ai is proud to be an Equal Employment Opportunity employer. We prohibit discrimination based on race, religion, color, national origin, sex, pregnancy, reproductive health decisions or related medical conditions, sexual orientation, gender identity, gender expression, age, veteran status, disability, genetic information, or other characteristics protected by applicable local, state or federal laws. Jerry.ai is committed to providing reasonable accommodations for individuals with disabilities in our job application process. If you need assistance or an accommodation due to a disability, please contact us at recruiting@jerry.ai recruiting@getjerry.com The successful candidate’s starting pay will fall within the pay range listed on this job posting, determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Ranges are market-dependent and may be modified in the future. In addition to base salary, the compensation may include opportunities for equity grants. We offer a comprehensive benefits package to regular employees, including health, dental, and vision coverage, paid time off, paid parental leave, 401(K) plan with employer matching, and wellness benefits, among others. Equity opportunities may also be part of your total rewards package. Part-time, contract, or freelance roles may not be eligible for certain benefits. About Jerry.ai Jerry.ai is America’s first and only super app to radically simplify car ownership. We are redefining how people manage owning a car, one of their most expensive and time-consuming assets. Backed by artificial intelligence and machine learning, Jerry.ai simplifies and automates owning and maintaining a car while providing personalized services for all car owners' needs. We spend every day innovating and improving our AI-powered app to provide the best possible experience for our customers. From car insurance and financing to maintenance and safety, Jerry.ai does it all. We are the #1 rated and most downloaded app in our category with a 4.7 star rating in the App Store. We have more than 5 million customers — and we’re just getting started. Jerry.ai was founded in 2017 by serial entrepreneurs and has raised more than $240 million in financing. Join our team and work with passionate, curious and egoless people who love solving real-world problems. 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Develop tools, Develop evals, Develop analyses, Develop playbooks, Serve as advisor, Evaluate new use cases, Discuss AI risk status, Report AI risk status, Champion AI", "teamCollaboration" : "First-line teams; Second line of defense; Third line of defense; Senior managers; Stakeholders", "projectManagementSkills" : [ "Agile" ], "domainKnowledge" : "AI quality; Agentic behavior; Platform cybersecurity; Data privacy; Fraud-specific matters; RAG pipelines; Tool use; Autonomy boundaries; Human oversight; Hallucination risk; Model drift; Model instability; Fairness; Robustness; SR 11-7; SR 26-2; OCC 2011-12; NIST AI RMF; EU AI Act", "domainList" : [ "ai-quality", "agentic-behavior", "platform-cybersecurity", "data-privacy", "fraud-specific-matters", "rag-pipelines", "tool-use", "autonomy-boundaries", "human-oversight", "hallucination-risk", "model-drift", "model-instability", "fairness", "robustness", "sr-11-7", "sr-26-2", "occ-2011-12", "nist-ai-rmf", "eu-ai-act" ], 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"qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, Dbt Certified", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "ABOUT NU Nu is one of the largest digital financial services platforms in the world, serving 135 million customers across Brazil, Mexico, and Colombia. The company has been leading an industry transformation by leveraging data and proprietary technology to develop innovative products and services. Guided by its mission to fight complexity and empower people, Nu caters to customers’ complete financial journey, promoting financial access and advancement with responsible lending and transparency. The company is powered by an efficient and scalable business model that combines low cost to serve with growing returns. Nu’s impact has been recognized in multiple awards, including Time 100 Most Influential Companies, Fast Company’s Most Innovative Companies, and Forbes World’s Best Banks. Visit our institutional page: https://www.nu.com/2026-en ABOUT US Nu is one of the largest digital financial platforms in the world, with more than 122 million customers across Brazil, Mexico, and Colombia. Guided by our mission to fight complexity and empower people, we are redefining financial services in Latin America and this is still just the beginning of the purple future we're building. Listed on the New York Stock Exchange (NYSE: NU), we combine proprietary technology, data intelligence, and an efficient operating model to deliver financial products that are simple, accessible, and human. Our impact has been recognized by global rankings such as Time 100 Companies, Fast Company’s Most Innovative Companies, and Forbes World’s Best Bank. Visit our institutional page https://international.nubank.com.br/careers/ About the team At Nubank we heavily rely on Data, Machine Learning, and increasingly on Generative and Agentic AI to drive our strategy and deliver the best experience and products to our customers. The Model Risk team plays a crucial role in ensuring the risks associated with our models and AI systems are understood and under control. We are now building a dedicated AI Risk Management capability to address the emerging risks of advanced AI — including LLM-powered and autonomous agentic systems — with a focus on AI quality, model and agent behavior, and the platform controls that keep these systems safe and reliable across internal and customer-facing use cases. About the role This is a senior, hands-on technical position. You will help define what model risk management looks like for AI and Agentic AI at Nubank — building and enhancing the frameworks, not just inheriting them. You will perform independent assessments of AI systems for quality, behavior, and robustness, and help design the guardrails and platform-level controls that govern their safe use. You'll act as a credible technical peer to first-line engineering and AI development teams, providing practical guidance on AI risk without slowing responsible innovation. This role focuses on AI quality, agentic behavior, and platform controls; cybersecurity, data privacy, and fraud-specific matters sit with partner functions and are out of scope. What you will do AI Risk Framework & Governance - Build and continuously enhance the risk management framework for AI and Agentic AI systems, including inventory standards, assessment methodologies, control design, and issue management. - Inventory and map Nubank's AI use cases to surface gaps, materiality, and the most critical risks, and define prioritized mitigation actions. - Assess whether first-line monitoring is effective, proportionate to model risk, and sufficient to keep AI systems fit for purpose over time. Independent AI Assessment - Perform independent technical assessments across generative AI, and agentic workflows, covering data, assumptions, methodology, testing, behavior, and monitoring. - Assess risks in LLM-powered applications, including RAG pipelines, tool use, autonomy boundaries, model/agent quality, human oversight, and hallucination risk. - Identify and document model limitations, failure modes, and emerging AI risks, including drift, instability, fairness, and robustness concerns. Controls, Platform & Enablement - Influence first-line teams on platform architecture and embedded controls for the safe deployment and monitoring of AI. - Build Key Risk Indicators (KRIs) and metrics for continuous monitoring of AI risk. - Develop tools, evals, analyses, and playbooks (including AI-enabled automation) to improve the speed, scale, and effectiveness of AI governance and validation. Advisory & Advocacy - Serve as a trusted advisor across the AI/ML lifecycle, evaluating new use cases for materiality and governance requirements prior to deployment. - Discuss and report AI risk status and independent opinions to stakeholders, including senior managers and, where relevant, regulators. - Champion AI risk management as a strategic enabler of safe and scalable AI adoption, and build AI risk literacy across engineering, product, and risk teams. - Work in a multicultural, diverse, and highly skilled environment. Requirements we are looking for - Education: A bachelor's or master's degree in a quantitative field (computer science, data science, statistics, mathematics, engineering, or related). - Hands-on AI/ML experience: A track record developing or validating AI/ML models and systems, ideally a candidate who has moved from an AI / Machine Learning Engineer background into model risk, governance, or risk management. You don't need to have trained foundation models from scratch, but you need solid, current technical depth. - Strong technical foundations: Proficiency in Python, SQL, and modern ML tooling; familiarity with LLMs, RAG systems, prompt engineering, and AI agent frameworks. - Evaluation and testing: Experience evaluating and testing ML and generative AI systems, including custom evals, benchmarking, stress testing, and drift/degradation monitoring. - Risk management experience: Demonstrated experience in risk identification, control definition, and framework building; understanding of model risk governance principles and independent effective challenge. - Data skills: Experience working with large datasets and building dashboards and analyses to support risk visibility. - High agency and adaptability: Comfortable operating in ambiguity, synthesizing fragmented technical and business context into a clear view of how complex AI systems actually work, and making sound judgments without a complete playbook. - Influencing skills: Able to engage and align stakeholders across first and second lines of defense as a credible technical peer. - Communication: Strong written and verbal skills, you can explain AI risk to a data scientist and to a regulator, and use different language for each. - Advanced or fluent English: You will meet with partners and stakeholders across countries and prepare documentation and presentations in English. - PLUS: Experience in a 2nd or 3rd line of defense. - PLUS: Familiarity with regulatory Model Risk Management and AI frameworks (e.g., SR 11-7 / SR 26-2 / OCC 2011-12, NIST AI RMF, EU AI Act). Benefits - Opportunity of earning equity at Nu - Medical Insurance - Dental and Vision Insurance - Life Insurance and AD&D - Extended maternity and paternity leaves - Nucleo - Our learning platform of courses - NuLanguage - Our language learning program - NuCare - Our mental health and wellness assistance program - Extended maternity and paternity leaves - 401K - Saving Plans - Health Saving Account and Flexible Spending Account - Work-from-home Allowance - Relocation Assistance Package, if applicable. WORK MODEL FOR THIS ROLE Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/ By submitting an application, I acknowledge that I have read and understand the Nubank Candidate Privacy Notice. Nubank Candidate Privacy Notice (English https://building.nubank.com/privacy-notice-for-candidates// Portuguese https://building.nubank.com/pt-br/aviso-de-privacidade-para-candidatos/ / Spanish). https://nu.com.mx/aviso-de-privacidad-candidatos/", "summaryDescription" : "AI and Agentic AI Risk Management Senior Specialist at Nu. Skills: AI Risk Management, Agentic AI Risk, Model Risk Management, Generative AI. Build risk management framework. Enhance risk management framework", "createdAt" : "2026-06-13T23:50:19.096", "lastUpdated" : "2026-06-15T11:53:12.381", "ingestTimestamp" : "2026-06-13T23:50:19.096", "mongoId" : "6a2cb05a74d8ee00a09d9b1f", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 155000, "salaryAnnualMax" : 230000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Regression", "Classification", "Clustering", "Time-series", "A/B testing", "Causal inference", "AI quality", "Agent behavior", "Model behavior", "Platform controls", "Data privacy", "Fraud detection", "Agency", "Adaptability", "Influencing", "AI Risk Management", "Agentic AI Risk", "Model Risk Management", "Generative AI", "Risk management", "Model risk", "AI risk", "Agentic AI", "LLM", "Data governance", "Platform architecture", "Quantitative analysis", "Agile", "Agentic behavior", "Platform cybersecurity", "Fraud-specific matters", "RAG pipelines", "Tool use", "Autonomy boundaries", "Human oversight", "Hallucination risk", "Model drift", "Model instability", "Fairness", "Robustness", "SR 11-7", "SR 26-2", "OCC 2011-12", "NIST AI RMF", "EU AI Act", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy", "SageMaker", "Vertex AI", "ML Studio" ], "skillCount" : 64, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 475.31448, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.97 }, { "id" : "6a2cdb6974d8ee00a0a504aa", "title" : "Generative Artist", "company" : "Sphere Entertainment Group", "industry" : "Media", "salary" : { "min" : 96000.0, "max" : 165000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Burbank, California, United States", "locations" : [ "Burbank", "California", "United States" ], "timestamp" : "2026-06-15T07:45:23.767", "fingerprint" : "0d7ee552783299c4213951e34c559762c1a73a581cc4a08fc5ee3731dfc7aa01", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://www.sphereentertainmentco.com/job/5161682007?gh_jid=5161682007", "externalId" : "5161682007", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Burbank", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "34.1812089,-118.3072010" } ], "locationText" : "Burbank, California, United States", "employmentType" : "FULL_TIME", "technicalSkills" : "Generative AI, AI, Compositing", "professionalSkills" : [ "Creative problem solving" ], "hardSkillsList" : [ "Prompt engineering", "Asset preparation", "Nodegraph creation", "Compositing workflows" ], "softSkillsList" : [ "Innovative", "Good communicators" ], "hardSkills" : [ { "name" : "Prompt engineering", "level" : "intermediate" }, { "name" : "Asset preparation", "level" : "intermediate" }, { "name" : "Nodegraph creation", "level" : "intermediate" }, { "name" : "Compositing workflows", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Innovative" }, { "name" : "Good communicators" } ], "majorSkills" : "Generative AI, Prompt engineering, Compositing", "majorSkillsList" : [ "Generative AI", "Prompt engineering", "Compositing" ], "coreResponsibilities" : "Generate AI outputs, Iterate AI outputs, Refine AI outputs, Write prompts, Refine prompts, Create start frames, Create end frames, Perform post processing, Composite AI imagery, Publish versioned assets, Maintain organized asset libraries, Maintain file naming conventions, Maintain version control, Run Gen AI tests", "teamCollaboration" : "Creative leadership; Design leadership; Production leadership; Post Production leadership; Visual Effects leadership; Playback leadership; Experiential Production leadership; Generative Effects team", "domainKnowledge" : "Immersive experiences; Large screens; Generative Effects", "domainList" : [ "immersive-experiences", "large-screens", "generative-effects" ], "domainSpecificKnowledge" : [ "Immersive experiences", "Large screens", "Generative Effects" ], "toolProficiency" : [ "ComfyUI", "Photoshop", "Nuke", "ShotGrid" ], "innovationCreativity" : "Exploring new language for Sphere", "qualificationsBasic" : "Expert level skills in prompt engineering, Expert level skills in asset preparation, Expert level skills in nodegraph creation, Expert level skills in Gen AI post processing, Expert level skills in compositing workflows", "qualificationsPreferred" : "Passion for creating using AI", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Sphere Entertainment Co. is a leader in immersive experiences, technology and media. The Company includes Sphere, an experiential medium powered by advanced technologies. The first Sphere opened in Las Vegas, with a second venue planned for Abu Dhabi. In addition, the Company includes MSG Networks, which operates two regional sports and entertainment networks, MSG Network and MSG Sportsnet, as well as a direct-to-consumer and authenticated streaming product, MSG+, delivering a wide range of live sports content and other programming. More information is available at www.sphereentertainmentco.com. Who are we hiring? Enthusiastic, skilled and reliable Generative Artist with passion for creating using AI to enable content creation for the largest screens in the world! This Generative Artist reports to the Generative Effects Supervisor and works across every aspect of AI-driven production: prompt engineering, asset preparation, nodegraph based creation tools, post processing of Gen AI outputs, compositing workflows, etc. with expert level skills in one or more of those areas. Working closely with leadership in Creative, Design, Production, Post Production, Visual Effects, Playback and Experiential Production, this position is ideal for innovative artists who are good communicators with a positive attitude and great creative problem solving skills. This role is part of a Generative Effects team exploring and developing a new and unique language for Sphere. What will you do? Execute creative briefs by generating, iterating, and refining AI outputs to meet directorial needs and creative vision. Write and refine prompts to feed into Gen AI models, running tools like or similar to ComfyUI and iterating on outputs to match directorial notes. Create start and end frames in Photoshop and other Gen AI tools to establish creative direction for sequences. Perform post-processing and compositing of AI-generated imagery in Nuke, combining generative outputs with traditional production techniques. Publish versioned assets to ShotGrid for supervisor review and approval. Maintain organized asset libraries, file naming conventions, and version control within the team's production environment. Proactively run Gen AI tests in collaboration with the Sr. Director of Production adaptability to new pipelines and utilization of provided tools is critical. #LI-Onsite Pay Range $96,000—$165,000 USD At MSG, we recognize the importance of upskilling employees’ talents and strengths so they can drive their careers forward. We are proud to offer a robust set of tools and resources to help employees understand their interests and purpose, harness their talents and obtain the skills they need to reach the next step in their careers. Growth and longevity for our employees are top priorities here. We value diversity and are looking for extraordinary employees of all backgrounds! MSG is an Equal Opportunity Employer and provides equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, sexual and reproductive health choices, national origin, citizenship, age, genetic information, disability, or veteran status. MSG complies with all applicable federal, state, and local laws governing nondiscrimination, including considering requests for reasonable accommodations as required.", "summaryDescription" : "Generative Artist at Sphere Entertainment Group. Skills: Generative AI, Prompt engineering, Compositing. Generate AI outputs. Iterate AI outputs", "postedDate" : "2026-06-13T22:30:45.201", "createdAt" : "2026-06-13T22:30:45.201", "lastUpdated" : "2026-06-15T07:45:23.767", "ingestTimestamp" : "2026-06-13T22:30:45.201", "mongoId" : "6a2cdb6974d8ee00a0a504aa", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 96000, "salaryAnnualMax" : 165000, "salaryBand" : "75k-100k", "hasSalary" : true, "allSkills" : [ "Prompt engineering", "Asset preparation", "Nodegraph creation", "Compositing workflows", "Innovative", "Good communicators", "Generative AI", "Compositing", "Creative problem solving", "Immersive experiences", "Large screens", "Generative Effects", "ComfyUI", "Photoshop", "Nuke", "ShotGrid" ], "skillCount" : 16, "jobCategory" : "product", "jobSubcategory" : "design", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "_score" : 473.24118, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Media", "llmIndustryConfidence" : 0.95 }, { "id" : "6a30876cf292fd229c088d53", "title" : "Machine Learning Engineer, Next-Generation Recommendation Systems (New Grad / PhD)", "company" : "Unity Technologies", "industry" : "Technology", "salary" : { "min" : 112700.0, "max" : 169100.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, NY, USA", "locations" : [ "New York", "NY", "USA" ], "certifications" : [ "GCP Professional Data Engineer certification", "AWS Data Analytics certification", "Databricks Certified certification", "Dbt Certified certification" ], "timestamp" : "2026-06-16T12:36:05.865", "fingerprint" : "0867ba40da51d162ee8ae4073923097c2ea972d8898ffbe1818eefa6d825a9fe", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://unity.com/careers/positions/7999719?gh_jid=7999719", "externalId" : "7999719", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "PhD", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "technicalSkills" : "SQL, Python, R, Scala, Spark, Dbt, Tableau, Power BI, Looker, Metabase, Superset, Qlik, MicroStrategy, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, GCP, Azure, S3, Glue, SageMaker, Athena, Vertex AI, Synapse, ML Studio", "professionalSkills" : [ "Data engineering", "Data science", "Machine learning", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Statistical modeling" ], "hardSkillsList" : [ "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B 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"BigQuery", "Redshift", "Databricks", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow", "AWS", "GCP", "Azure", "SageMaker", "Vertex AI", "ML Studio" ], "qualificationsBasic" : "SQL proficiency, Python proficiency", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification, Experience with scikit-learn, Experience with TensorFlow, Experience with PyTorch, Experience with XGBoost, Experience with LightGBM, Experience with Hugging Face, Experience with MLflow, Experience with Snowflake, Experience with BigQuery, Experience with Redshift, Experience with Databricks, Experience with dbt, Experience with Fivetran, Experience with Airflow, Experience with dbt Cloud, Experience with Delta Lake, Experience with AWS SageMaker, Experience with GCP Vertex AI, Experience with Azure ML Studio", "remoteFriendly" : false, "rawDescription" : "The opportunity Unity's Vector AI team builds the machine learning systems that decide which ads reach which players — across billions of monthly users on the world's leading game engine. Recommendation and ranking systems are the core of this work: predicting user value, optimizing bids, and delivering outcomes for advertisers at massive scale. We are building the next generation of these systems. The frontier has shifted — large language models, reinforcement learning from human feedback, and agentic AI are reshaping what recommendation systems can do. We are looking for PhD graduates who have worked at that frontier and want to bring those ideas into production systems that matter. What you'll be doing Design, build, and evaluate next-generation ranking and recommendation models that incorporate LLMs, RLHF, and preference learning to improve ad relevance and user experience. Develop user understanding systems — conversion prediction, behavioral modeling, and value estimation — that operate across billions of impressions. Apply reinforcement learning and optimization techniques to bidding strategy, auction dynamics, and real-time ad delivery. Design and run rigorous experiments using causal inference, A/B testing, and offline evaluation frameworks to measure and improve model quality. Partner with engineering to bring research ideas into production, working across the full pipeline from training data to deployed model. Communicate findings clearly to technical and non-technical stakeholders across engineering, product, and business teams. What we're looking for PhD in Computer Science, Machine Learning, Statistics, or a related field (graduating 2026 or recent graduate). Strong research foundations in one or more of: recommendation systems, reinforcement learning, LLM post-training or alignment, human-AI collaboration, probabilistic modeling, or optimization. Experience working with large-scale data and ML systems, whether through research or industry internships. Fluency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow. A track record of rigorous, high-quality research — publications at top venues (NeurIPS, ICML, ICLR, KDD, RecSys, ACL, WWW, or similar) are a strong signal. Strong written and verbal communication skills — able to make complex ideas accessible across technical and non-technical audiences. You might also have Industry experience in ads, recommendation, or user understanding systems (internship experience counts). Hands-on experience with production ML pipelines — training at scale, feature engineering, or experimentation infrastructure. Experience applying LLMs or generative models to ranking, retrieval, or structured prediction problems. Familiarity with agentic AI approaches — multi-step reasoning, tool use, or human-AI collaboration frameworks. Exposure to causal inference, uplift modeling, or A/B testing at scale. Genuine curiosity about applied research and the drive to see ideas through to impact. Additional information Relocation support is not available for this position Benefits At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance. Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status. While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program Life at Unity Unity [NYSE: U] is the world’s leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D — closing the gap between ideas and reality. For more information, please visit www.unity.com. Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know. This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English. Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity. Your privacy is important to us. Please take a moment to review our Prospect Privacy Policy and Applicant Privacy Policy. Should you have any concerns about your privacy, please contact us at DPO@unity.com. #MID #LI-ED1 *Note: This range reflects the anticipated base salary for this position. Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount will depend on several factors, including geographic location and the candidate’s relevant experience, professional background, and skill set. Gross pay salary $112,700—$169,100 USD", "summaryDescription" : "Machine Learning Engineer, Next-Generation Recommendation Systems (New Grad / PhD) at Unity Technologies. Skills: Data science, Machine learning, Data engineering", "postedDate" : "2026-06-16T01:21:50.550", "createdAt" : "2026-06-16T01:21:50.550", "lastUpdated" : "2026-06-16T12:36:05.865", "ingestTimestamp" : "2026-06-16T01:21:50.550", "mongoId" : "6a30876cf292fd229c088d53", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 112700, "salaryAnnualMax" : 169100, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference", "Data science", "Machine learning", "Data engineering", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Statistical modeling", "GCP Professional Data Engineer certification", "AWS Data Analytics certification", "Databricks Certified certification", "Dbt Certified certification", "SQL", "Python", "R", "Scala", "Spark", "Dbt", "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy", "Snowflake", "BigQuery", "Redshift", "Databricks", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow", "AWS", "GCP", "Azure", "SageMaker", "Vertex AI", "ML Studio" ], "skillCount" : 56, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 1.0, "_score" : 469.96484, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c692474d8ee00a0906355", "title" : "Omnichannel Recommendations - GTM Specialist", "company" : "Constructor", "industry" : "Sales", "salary" : { "min" : 115000.0, "max" : 165000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Omnichannel Recommendations - GTM Specialist in the United States, adjusted for the e-commerce industry and remote work." }, "location" : "Remote - United States", "locations" : [ "Remote - United States" ], "timestamp" : "2026-06-16T02:20:26.371", "fingerprint" : "36c52db9ed6fa124bcd5c6475d5ffe91f6b0451af28b91b8ff26d8838870fc75", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/constructor/75d52991-d469-44dc-960b-6dad26f903b9/application", "externalId" : "75d52991-d469-44dc-960b-6dad26f903b9", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "ABOUT US Constructor is the next-generation platform for search and discovery in ecommerce, built to explicitly optimize for metrics like revenue, conversion rate, and profit. Our search engine is entirely invented in-house utilizing transformers and generative LLMs, and we use its core and personalization capabilities to power everything from search itself to recommendations to shopping agents. Engineering is by far our largest department, and we’ve built our proprietary engine to be the best on the market, having never lost an A/B test to a competitive technology. We’re passionate about maintaining this and work on the bleeding edge of AI to do so. Out of necessity, our engine is built for extreme scale and powers over 1 billion queries every day across 150 languages and roughly 100 countries. It is used by some of the biggest ecommerce companies in the world like Sephora, Under Armour, and Petco. We’re a passionate team who love solving problems and want to make our customers’ and coworkers’ lives better. We value empathy, openness, curiosity, continuous improvement, and are excited by metrics that matter. We believe that empowering everyone in a company to do what they do best can lead to great things. Constructor is a U.S. based company that has been in the market since 2019. It was founded by Eli Finkelshteyn and Dan McCormick who still lead the company today. ABOUT THE ROLE As we expand our personalization and messaging capabilities, we are looking for a foundational member of our growing team. The Offsite Recommendations Strategist owns the activation, performance, and revenue growth of our AI-powered email recommendations offering. This is a revenue-generating, client-facing role with incentive-based compensation. You will serve as a strategic partner to retail and e-commerce clients, helping them design, launch, and scale high-performing recommendation-driven email programs across promotional, triggered, and lifecycle messaging. From first deployment through long-term expansion, you will guide customers in using intelligent recommendations to drive measurable gains in engagement, conversion, and lifetime value. WHAT YOU’LL DO - Own onboarding and activation for offsite recommendations, partnering with Sales, Account Management, Customer Success, Solutions, and Marketing teams. - Guide clients through ESP integrations, feed setup, and recommendation placement in email templates. - Advise on high-impact email use cases including: - Promotional campaigns - Browse & cart abandonment - Post-purchase and replenishment - Lifecycle and retention programs - Serve as the subject-matter expert on email personalization and recommendations. - Analyze performance and provide data-driven recommendations to improve CTR, conversion, AOV, revenue per send, and LTV. - Own revenue growth across a portfolio of customers through upsell, expansion, and new use cases. - Act as the voice of the customer, influencing product roadmap and go-to-market strategy. REQUIREMENTS - 1-3 years of hands-on email or lifecycle marketing experience, ideally in e-commerce or retail. - 3-5+ years of client-facing experience in sales, account management, customer success, or account strategy - Strong understanding of: - ESPs and email ecosystems - Segmentation, personalization, and lifecycle strategy - Campaign vs. triggered messaging - Testing and performance measurement - Experience working with AI-driven personalization or recommendation systems. - Proven ability to translate data into insights and business impact. - Client-facing experience with a consultative, growth-oriented mindset. - Track record of driving or influencing revenue growth from existing customers. - Excellent communication skills and comfort working with both operators and executives. BENEFITS - \uD83C\uDFDD️ Unlimited vacation time -we strongly encourage all of our employees take at least 3 weeks per year - \uD83D\uDCB0 A competitive compensation package including stock options - \uD83C\uDF0E Fully remote team - choose where you live - \uD83D\uDECB️ Work from home stipend! We want you to have the resources you need to set up your home office - \uD83D\uDCBB Apple laptops provided for new employees - \uD83E\uDDD1‍\uD83C\uDF93 Training and development budget for every employee, refreshed each year - \uD83D\uDC6A Parental leave for qualified employees - \uD83E\uDDE0 Work with smart people who will help you grow and make a meaningful impact DIVERSITY, EQUITY, AND INCLUSION AT CONSTRUCTOR At Constructor.io http://Constructor.io we are committed to cultivating a work environment that is diverse, equitable, and inclusive. As an equal opportunity employer, we welcome individuals of all backgrounds and provide equal opportunities to all applicants regardless of their education, diversity of opinion, race, color, religion, gender, gender expression, sexual orientation, national origin, genetics, disability, age, veteran status or affiliation in any other protected group. Studies have shown that women and people of color may be less likely to apply for jobs unless they meet every one of the qualifications listed. Our primary interest is in finding the best candidate for the job. We encourage you to apply even if you don’t meet all of our listed qualifications.", "summaryDescription" : "Omnichannel Recommendations - GTM Specialist at Constructor", "createdAt" : "2026-06-14T20:11:11.615", "lastUpdated" : "2026-06-16T02:20:26.371", "ingestTimestamp" : "2026-06-14T20:11:11.615", "mongoId" : "6a2c692474d8ee00a0906355", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 115000, "salaryAnnualMax" : 165000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "sales", "jobSubcategory" : "revenue", "seniorityLevel" : "Mid", "dataQualityScore" : 0.6666667, "_score" : 469.9296, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "E-Commerce", "llmIndustryConfidence" : 0.95 }, { "id" : "6a3074d9f292fd229c009d20", "title" : "Director, Data and AI Engineering", "company" : "Benevity", "industry" : "Technology", "salary" : { "min" : 175000.0, "max" : 250000.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline data for Director, Data and AI Engineering in Calgary, Canada, adjusted for SaaS industry and company size." }, "location" : "Calgary, Alberta", "locations" : [ "Calgary, Alberta", "Vancouver, British Columbia" ], "timestamp" : "2026-06-16T11:55:49.932", "fingerprint" : "48d6e9e7d6092e824c8f4e626ef408c40aef8877a09c5443b28ff1eaf3b039e9", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/benevity/863fc534-814d-4aed-a969-d52dd5e43dc2/application", "externalId" : "863fc534-814d-4aed-a969-d52dd5e43dc2", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Calgary", "state" : "Alberta", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "51.0456064,-114.0575410" } ], "locationText" : "Calgary, Alberta, Canada", "employmentType" : "FULL_TIME", "experienceLevel" : "Director", "remoteFriendly" : true, "rawDescription" : "MEET BENEVITY Benevity is the way the world does good, providing companies (and their employees) with technology to take social action on the issues they care about. Through giving, volunteering, grantmaking, employee resource groups and micro-actions, we help most of the Fortune 100 brands build better cultures and use their power for good. We’re also one of the first B Corporations in Canada, meaning we’re as committed to purpose as we are to profits. We have people working all over the world, including Canada, Spain, Switzerland, the United Kingdom, the United States and more! We are seeking a Director of Data and ML/AI Engineering to lead our data and AI technology strategy, architecture, and execution within our B2B SaaS Benevity Impact Platform. This role is pivotal in enabling data-driven decision-making, product intelligence, and AI-powered services and automation across our platform. The ideal candidate will have deep expertise in scalable data engineering, AI/ML systems and services, and cloud-based data architectures, with a track record of building highly available, real-time analytics, and ML/AI-driven solutions for SaaS platforms. This role will oversee data science, data modeling, business intelligence, governance, and ML/AI systems engineering, ensuring alignment with our client and business needs. What you’ll do: Leadership & Data Strategy - Define and execute the data and AI strategy for our SaaS platform, ensuring alignment with business objectives and customer needs. - Lead cross-functional teams across data engineering, AI/ML, BI, and governance to deliver scalable, high-impact solutions. - Establish data-as-a-product principles, ensuring data assets are secure, reusable, and monetizable within our platform. - Drive innovation in real-time analytics, AI-powered automation and intelligence for clients. - Partner with Product, Engineering, and Customer Success teams to enhance data-driven insights, reporting, and self-service analytics. Data Engineering & Platform Architecture - Design and oversee high-scale, cloud-native data architectures that support real-time streaming, data lakes / lakehouses, and enterprise warehousing. - Implement highly available, fault-tolerant data pipelines to process, store, and serve insights across the platform. - Lead data modeling initiatives to optimize data structures for analytics, ML training, and business reporting. - Work with engineering teams to embed AI-powered features into the SaaS platform, enabling smart automation, anomaly detection, and personalization. - Drive observability, monitoring, and cost optimization across our cloud-based data infrastructure. AI/ML Engineering & Data Science - Oversee the development of ML/AI models, ensuring they are scalable, explainable, and deployed effectively in production. - Implement MLOps best practices, including CI/CD for models, versioning, and real-time inference. - Lead initiatives in AI-powered recommendations, predictive analytics, NLP, and generative AI to enhance our product offerings. - Ensure bias-free, ethical AI practices and compliance with industry AI standards and regulations. Business Intelligence & Product Analytics - Build and manage BI tools, dashboards, and self-service analytics to provide real-time insights to clients and internal stakeholders. - Develop product analytics frameworks, tracking user behavior, adoption, and feature engagement. - Implement embedded analytics solutions that allow clients to gain actionable insights from their data. - Optimize reporting for SaaS metrics (MRR, ARR, churn, retention, LTV, NPS) and drive data-informed decision-making. Data Governance & Compliance - Own data governance frameworks, ensuring data privacy, security, and compliance (GDPR, SOC 2, PIPEDA, CCPA, etc.). - Define and implement data lineage, metadata management, and master data management (MDM) best practices. - Drive role-based access controls (RBAC, ABAC or ReBac) and ensure secure, auditable data sharing within our SaaS ecosystem. - Champion data democratization, enabling teams to access trusted, well-documented data. What you’ll bring: - 10+ years of experience in data engineering, AI/ML, or analytics leadership roles, ideally in B2B SaaS or cloud-based platforms - Strong expertise in scalable data architectures, ML/AI systems, and embedded analytics - Proven track record in leading high-performance teams, managing budgets, and delivering data-driven product innovations - Experience with multi-tenant SaaS data governance, compliance (SOC 2, GDPR, etc.), and customer-facing analytics - Familiarity with emerging AI trends, including LLMs, Generative AI, and responsible AI frameworks - Familiarity with SaaS product analytics and AI-powered automation use cases - Master’s or PhD in Computer Science, Data Science, AI/ML, or a related field is preferred Technical Skills & Expertise - Data & AI Stacks (Cloud-Native, SaaS-Optimized) - Data Engineering & Storage: BigQuery, Redshift, Delta Lake, Snowflake, Databricks - AI/ML Frameworks: Azure AI, TensorFlow, PyTorch, Hugging Face, MLflow, Vertex AI - MLOps & Pipelines: Kubeflow, SageMaker, Airflow, Feature Stores, DataRobot - BI & Analytics Tools: Looker, Power BI, Mode Analytics, Amplitude, Mixpanel - Data Governance & Security: Collibra, Informatica, Alation, Immuta - Cloud & DevOps: AWS (S3, Lambda, Kinesis), GCP (BigQuery, Pub/Sub), Kubernetes, Terraform - Programming: Python, SQL, Scala, Java - Streaming & Real-Time Data: Kafka, Flink, Apache Beam DISCOVER YOUR PURPOSE AT WORK We’re not employees, we’re Benevity-ites. From all locations, backgrounds and walks of life, who deserve more … Innovative work. Growth opportunities. Caring co-workers. And a chance to do work that fills us with a sense of purpose. If the idea of working on tech that helps people do good in the world lights you up ... If you want a career where you’re valued for who you are and challenged to see who you can become … It’s time to join Benevity. We’re so excited to meet you. WHERE WE WORK At Benevity, we embrace a flexible hybrid approach to where we work that empowers our people in a way that supports great work, strong relationships, and personal well-being. For those located near one of our offices, while there’s no set requirement for in-office time, we do value the moments when coming together in person helps us build connection and collaboration. Whether it’s for onboarding, project work, or a chance to align and bond as a team, we trust our people to make thoughtful decisions about when showing up in person matters most. JOIN A COMPANY WHERE DEIB ISN’T A BUZZWORD Diversity, equity, inclusion and belonging are part of Benevity’s DNA. You’ll see the impact of our massive investment in DEIB daily — from our well-supported employee resources groups to the exceptional diversity on our leadership and tech teams. We know that diverse backgrounds, experiences, skills and passions are what move our business and our people forward, so we're committed to creating a culture of belonging with equal opportunities for everyone to shine. That starts with a fair and accessible hiring process. If you want to feel seen, heard and celebrated, you belong at Benevity. Candidates with disabilities who may require accommodations throughout the hiring or assessment process are encouraged to reach out to accommodations@benevity.com.", "summaryDescription" : "Director, Data and AI Engineering at Benevity", "createdAt" : "2026-06-16T00:25:36.052", "lastUpdated" : "2026-06-16T11:55:49.932", "ingestTimestamp" : "2026-06-16T00:25:36.052", "mongoId" : "6a3074d9f292fd229c009d20", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "150k-200k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Director", "dataQualityScore" : 0.7777778, "_score" : 468.45105, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "SaaS", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6ace74d8ee00a090e166", "title" : "Generative 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" : "2026-06-15T10:26:41.493", "fingerprint" : "f21df527bfa9586cbe0b0249f3ce5fb5e9176e8c153334ea73f4c2d0a96e4ee7", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4234815009", "externalId" : "4234815009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "High School", "technicalSkills" : "Generative AI, Large Language Models, AI models, Machine learning models", "professionalSkills" : [ "Data engineering" ], "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Data compilation", "Text summarization", "Speech to text", "Translation" ], "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" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Speech to text", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" } ], "majorSkills" : "Generative AI, LLM development", "majorSkillsList" : [ "Generative AI", "LLM development" ], "coreResponsibilities" : "Rate/assess AI model performance, Label content elements, Assign predefined categories, Evaluate content quality, Generate labels for concepts, Create training data, Modify images, Generate new text, Alter audio/video signals, Review data for product features, Label model outputs, Identify content types, Order or rank items, Create prompts for AI, Evaluate content relevance, Generate responses to prompts, Rewrite existing text, Produce text summaries, Convert audio to text, Translate content, Gather and compile data", "teamCollaboration" : "Global contributor community; SME 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 (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 Generative AI 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 $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" : "Generative AI Annotator at Innodata Inc.. Skills: Generative AI, LLM development. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T09:25:50.192", "createdAt" : "2026-06-14T09:25:50.192", "lastUpdated" : "2026-06-15T10:26:41.493", "ingestTimestamp" : "2026-06-14T09:25:50.192", "mongoId" : "6a2c6ace74d8ee00a090e166", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 18720, "salaryBand" : "<30k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Data compilation", "Text summarization", "Speech to text", "Translation", "Generative AI", "LLM development", "Data engineering", "Large Language Models" ], "skillCount" : 12, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 466.552, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6ace74d8ee00a090e168", "title" : "Generative 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" : "2026-06-15T08:39:22.482", "fingerprint" : "f43ea4a1f6b8015f6bd1d9c192b9cd07d5458d4fe72a888af93d6874ae28bf7a", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4234820009", "externalId" : "4234820009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "High School", "technicalSkills" : "Generative AI, Large Language Models, Machine Learning", "hardSkillsList" : [ "Data labeling", "Data transformation", "Content evaluation", "Prompt generation", "Text summarization", "Speech to text", "Translation", "Data gathering" ], "hardSkills" : [ { "name" : "Data labeling", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Content evaluation", "level" : "intermediate" }, { "name" : "Prompt generation", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Speech to text", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" } ], "majorSkills" : "Generative AI, LLM, Data annotation", "majorSkillsList" : [ "Generative AI", "LLM", "Data annotation" ], "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 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 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 Generative AI 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 $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" : "Generative AI Annotator at Innodata Inc.. Skills: Generative AI, LLM, Data annotation. Rate/assess AI model performance. Label content elements", "postedDate" : "2026-06-14T09:31:05.906", "createdAt" : "2026-06-14T09:31:05.906", "lastUpdated" : "2026-06-15T08:39:22.482", "ingestTimestamp" : "2026-06-14T09:31:05.906", "mongoId" : "6a2c6ace74d8ee00a090e168", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 18720, "salaryBand" : "<30k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Data transformation", "Content evaluation", "Prompt generation", "Text summarization", "Speech to text", "Translation", "Data gathering", "Generative AI", "LLM", "Data annotation", "Large Language Models" ], "skillCount" : 12, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 466.44592, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6ace74d8ee00a090e1a5", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T10:09:44.098", "fingerprint" : "a957d4fade7c4222f870ab6ea010bbbcc1891e7009ef02849ea18c91e68be239", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4248703009", "externalId" : "4248703009", "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", "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Text summarization", "Translation" ], "hardSkills" : [ { "name" : "Data labeling", "level" : "intermediate" }, { "name" : "Content evaluation", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Translation", "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 categories or labels, Evaluate content quality, Generate labels for concepts, Create training data, Apply data transformations, Review data for features, Label model outputs, Identify content types, Order or rank items, Create prompts for AI, Evaluate content relevance, Generate AI responses, Rewrite existing text, Produce text summaries, Convert audio to text, Translate languages, Gather data for AI models", "domainKnowledge" : "Artificial Intelligence; Large Language Models", "domainList" : [ "artificial-intelligence", "large-language-models" ], "domainSpecificKnowledge" : [ "Artificial Intelligence", "Large Language Models" ], "qualificationsBasic" : "Bachelor's degree in humanities, Professional English proficiency (C1/C2)", "qualificationsPreferred" : "Advanced degrees 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, LLM development, Data annotation. Rate AI model performance. Label content elements", "postedDate" : "2026-06-14T09:31:05.885", "createdAt" : "2026-06-14T09:31:05.885", "lastUpdated" : "2026-06-15T10:09:44.098", "ingestTimestamp" : "2026-06-14T09:31:05.885", "mongoId" : "6a2c6ace74d8ee00a090e1a5", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Text summarization", "Translation", "Generative AI", "LLM development", "Data annotation", "Artificial Intelligence", "Large Language Models" ], "skillCount" : 11, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 466.4459, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e1a3", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T08:49:01.091", "fingerprint" : "90ce7d637c537a799f82a0dffb13343f829203aebb4e61cb1a4ee003cafef4f0", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4248719009", "externalId" : "4248719009", "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", "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Text summarization", "Translation", "Data gathering" ], "hardSkills" : [ { "name" : "Data labeling", "level" : "intermediate" }, { "name" : "Content evaluation", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" }, { "name" : "Data gathering", "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 categories or labels, Evaluate content quality, Generate labels for concepts, Create training data, Apply data transformations, Review data for product features, Label model outputs, Identify branded content, Order or rank items, Create prompts for AI, Evaluate content relevance, Generate AI responses, Rewrite existing text, Produce text summaries, Convert audio to text, Translate languages, Gather data for AI models", "domainKnowledge" : "Artificial Intelligence; Large Language Models", "domainList" : [ "artificial-intelligence", "large-language-models" ], "domainSpecificKnowledge" : [ "Artificial Intelligence", "Large Language Models" ], "qualificationsBasic" : "Bachelor's degree in humanities, Professional English proficiency (C1/C2)", "qualificationsPreferred" : "Advanced degrees 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, LLM development, Data annotation. Rate AI model performance. Label content elements", "postedDate" : "2026-06-14T09:30:59.567", "createdAt" : "2026-06-14T09:30:59.567", "lastUpdated" : "2026-06-15T08:49:01.091", "ingestTimestamp" : "2026-06-14T09:30:59.567", "mongoId" : "6a2c6ace74d8ee00a090e1a3", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Text summarization", "Translation", "Data gathering", "Generative AI", "LLM development", "Data annotation", "Artificial Intelligence", "Large Language Models" ], "skillCount" : 11, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 466.44122, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e170", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T13:52:50.966", "fingerprint" : "10449e8a2ef9e1443794161337467c28bad166fff25784562ac002e7f9d898d8", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4248774009", "externalId" : "4248774009", "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", "Quantitative Analysis", "Business Intelligence", "Data Science", "Analytics Engineering" ], "hardSkillsList" : [ "Data Labeling", "Content Evaluation", "Data Transformation", "Data Gathering", "Data Compilation", "Text Summarization", "Translation", "Content Generation" ], "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" }, { "name" : "Text Summarization", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" }, { "name" : "Content Generation", "level" : "intermediate" } ], "majorSkills" : "Generative AI, Large Language Models, AI Model Evaluation", "majorSkillsList" : [ "Generative AI", "Large Language Models", "AI Model Evaluation" ], "coreResponsibilities" : "Rate AI model performance, Label content elements, Assign categories or labels, Evaluate content quality, Generate labels for concepts, Create training data, Apply data transformations, Review data for functionality, Label model outputs, Order or rank items, Create prompts for AI, Evaluate content relevance, Generate AI responses, Rewrite existing text, Produce text summaries, Convert audio to text, Translate languages, Gather data for AI models, Compile digital content", "domainKnowledge" : "Artificial Intelligence; AI Systems", "domainList" : [ "artificial-intelligence", "ai-systems" ], "domainSpecificKnowledge" : [ "Artificial Intelligence", "AI Systems" ], "qualificationsBasic" : "Bachelor's degree in humanities, Professional C1/C2 English proficiency", "qualificationsPreferred" : "Advanced degrees 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, Large Language Models, AI Model Evaluation. Rate AI model performance. Label content elements", "postedDate" : "2026-06-14T08:56:50.141", "createdAt" : "2026-06-14T08:56:50.141", "lastUpdated" : "2026-06-15T13:52:50.966", "ingestTimestamp" : "2026-06-14T08:56:50.141", "mongoId" : "6a2c6ace74d8ee00a090e170", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data Labeling", "Content Evaluation", "Data Transformation", "Data Gathering", "Data Compilation", "Text Summarization", "Translation", "Content Generation", "Generative AI", "Large Language Models", "AI Model Evaluation", "Data Engineering", "Quantitative Analysis", "Business Intelligence", "Data Science", "Analytics Engineering", "Artificial Intelligence", "AI Systems" ], "skillCount" : 18, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 465.41193, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a30876cf292fd229c088d52", "title" : "Machine Learning Engineer, Next-Generation Recommendation Systems (New Grad / PhD)", "company" : "Unity Technologies", "industry" : "Technology", "salary" : { "min" : 112700.0, "max" : 169100.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, NY, USA", "locations" : [ "New York", "NY", "USA" ], "certifications" : [ "GCP Professional Data Engineer certification", "AWS Data Analytics certification", "Databricks Certified certification", "Dbt Certified certification" ], "timestamp" : "2026-06-16T12:18:23.439", "fingerprint" : "5e5f2e0dc44c587b5ed49a146b58778d441dc227b991c38aa9c349a24e3dec0e", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://unity.com/careers/positions/7992078?gh_jid=7992078", "externalId" : "7992078", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "PhD", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "technicalSkills" : "SQL, Python, R, Scala, Spark, Dbt, Tableau, Power BI, Looker, Metabase, Superset, Qlik, MicroStrategy, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, GCP, Azure, S3, Glue, SageMaker, Athena, Vertex AI, Synapse, ML Studio", "professionalSkills" : [ "Data engineering", "Data science", "Machine learning", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Statistical modeling" ], "hardSkillsList" : [ "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Statistical methods", "level" : "intermediate" }, { "name" : "ML frameworks", "level" : "intermediate" }, { "name" : "BI platforms", "level" : "intermediate" }, { "name" : "Cloud data stacks", "level" : "intermediate" }, { "name" : "Modelling skills", "level" : "intermediate" }, { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Data science, Machine learning, Data engineering", "majorSkillsList" : [ "Data science", "Machine learning", "Data engineering" ], "coreResponsibilities" : "Develop and deploy machine learning models, Design and implement data pipelines, Build and maintain data infrastructure, Analyze large datasets, Develop dashboards and reports, Collaborate with cross-functional teams, Stay current with industry trends", "teamCollaboration" : "Cross-functional teams", "domainKnowledge" : "Recommendation systems", "domainList" : [ "recommendation-systems" ], "domainSpecificKnowledge" : [ "Recommendation systems" ], "toolProficiency" : [ "SQL", "Python", "R", "Scala", "Spark", "Dbt", "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy", "Snowflake", "BigQuery", "Redshift", "Databricks", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow", "AWS", "GCP", "Azure" ], "continuousLearning" : "Stay current with industry trends", "qualificationsBasic" : "SQL proficiency, Python proficiency", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification, Experience with scikit-learn, Experience with TensorFlow, Experience with PyTorch, Experience with XGBoost, Experience with LightGBM, Experience with Hugging Face, Experience with MLflow, Experience with Snowflake, Experience with BigQuery, Experience with Redshift, Experience with Databricks, Experience with dbt, Experience with Fivetran, Experience with Airflow, Experience with dbt Cloud, Experience with Delta Lake, Experience with AWS SageMaker, Experience with GCP Vertex AI, Experience with Azure ML Studio", "remoteFriendly" : false, "rawDescription" : "The opportunity Unity's Vector AI team builds the machine learning systems that decide which ads reach which players — across billions of monthly users on the world's leading game engine. Recommendation and ranking systems are the core of this work: predicting user value, optimizing bids, and delivering outcomes for advertisers at massive scale. We are building the next generation of these systems. The frontier has shifted — large language models, reinforcement learning from human feedback, and agentic AI are reshaping what recommendation systems can do. We are looking for PhD graduates who have worked at that frontier and want to bring those ideas into production systems that matter. What you'll be doing Design, build, and evaluate next-generation ranking and recommendation models that incorporate LLMs, RLHF, and preference learning to improve ad relevance and user experience. Develop user understanding systems — conversion prediction, behavioral modeling, and value estimation — that operate across billions of impressions. Apply reinforcement learning and optimization techniques to bidding strategy, auction dynamics, and real-time ad delivery. Design and run rigorous experiments using causal inference, A/B testing, and offline evaluation frameworks to measure and improve model quality. Partner with engineering to bring research ideas into production, working across the full pipeline from training data to deployed model. Communicate findings clearly to technical and non-technical stakeholders across engineering, product, and business teams. What we're looking for PhD in Computer Science, Machine Learning, Statistics, or a related field (graduating 2026 or recent graduate). Strong research foundations in one or more of: recommendation systems, reinforcement learning, LLM post-training or alignment, human-AI collaboration, probabilistic modeling, or optimization. Experience working with large-scale data and ML systems, whether through research or industry internships. Fluency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow. A track record of rigorous, high-quality research — publications at top venues (NeurIPS, ICML, ICLR, KDD, RecSys, ACL, WWW, or similar) are a strong signal. Strong written and verbal communication skills — able to make complex ideas accessible across technical and non-technical audiences. You might also have Industry experience in ads, recommendation, or user understanding systems (internship experience counts). Hands-on experience with production ML pipelines — training at scale, feature engineering, or experimentation infrastructure. Experience applying LLMs or generative models to ranking, retrieval, or structured prediction problems. Familiarity with agentic AI approaches — multi-step reasoning, tool use, or human-AI collaboration frameworks. Exposure to causal inference, uplift modeling, or A/B testing at scale. Genuine curiosity about applied research and the drive to see ideas through to impact. Additional information Relocation support is not available for this position Benefits At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance. Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status. While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program Life at Unity Unity [NYSE: U] is the world’s leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D — closing the gap between ideas and reality. For more information, please visit www.unity.com. Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know. This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English. Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity. Your privacy is important to us. Please take a moment to review our Prospect Privacy Policy and Applicant Privacy Policy. Should you have any concerns about your privacy, please contact us at DPO@unity.com. #MID #LI-ED1 *Note: This range reflects the anticipated base salary for this position. Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount will depend on several factors, including geographic location and the candidate’s relevant experience, professional background, and skill set. Gross pay salary $112,700—$169,100 USD", "summaryDescription" : "Machine Learning Engineer, Next-Generation Recommendation Systems (New Grad / PhD) at Unity Technologies. Skills: Data science, Machine learning, Data engineering. Develop and deploy machine learning models. Design and implement data pipelines", "postedDate" : "2026-06-16T01:21:03.300", "createdAt" : "2026-06-16T01:21:03.300", "lastUpdated" : "2026-06-16T12:18:23.439", "ingestTimestamp" : "2026-06-16T01:21:03.300", "mongoId" : "6a30876cf292fd229c088d52", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 112700, "salaryAnnualMax" : 169100, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference", "Data science", "Machine learning", "Data engineering", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Statistical modeling", "Recommendation systems", "GCP Professional Data Engineer certification", "AWS Data Analytics certification", "Databricks Certified certification", "Dbt Certified certification", "SQL", "Python", "R", "Scala", "Spark", "Dbt", "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy", "Snowflake", "BigQuery", "Redshift", "Databricks", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow", "AWS", "GCP", "Azure" ], "skillCount" : 54, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 1.0, "_score" : 464.71216, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a30876cf292fd229c088d54", "title" : "Machine Learning Engineer, Next-Generation Recommendation Systems (New Grad / PhD)", "company" : "Unity Technologies", "industry" : "Technology", "salary" : { "min" : 112700.0, "max" : 169100.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, NY, USA", "locations" : [ "New York", "NY", "USA" ], "certifications" : [ "GCP Professional Data Engineer certification", "AWS Data Analytics certification", "Databricks Certified certification", "Dbt Certified certification" ], "timestamp" : "2026-06-16T11:01:28.921", "fingerprint" : "8d11c9891b3bddb75bf0d97edd72d2426d03638ef2bd2548f74347cbab4c5a94", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://unity.com/careers/positions/7999717?gh_jid=7999717", "externalId" : "7999717", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "PhD", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "technicalSkills" : "SQL, Python, R, Scala, Spark, Dbt, Tableau, Power BI, Looker, Metabase, Superset, Qlik, MicroStrategy, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, GCP, Azure, S3, Glue, SageMaker, Athena, Vertex AI, Synapse, ML Studio", "professionalSkills" : [ "Data engineering", "Data science", "Machine learning", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Statistical modeling" ], "hardSkillsList" : [ "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Statistical methods", "level" : "intermediate" }, { "name" : "ML frameworks", "level" : "intermediate" }, { "name" : "BI platforms", "level" : "intermediate" }, { "name" : "Cloud data stacks", "level" : "intermediate" }, { "name" : "Modelling skills", "level" : "intermediate" }, { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Data science, Machine learning, Data engineering", "majorSkillsList" : [ "Data science", "Machine learning", "Data engineering" ], "coreResponsibilities" : "Develop and deploy machine learning models, Build and maintain data pipelines, Design and implement data warehousing solutions, Create and manage BI dashboards, Perform statistical analysis, Conduct quantitative research, Collaborate with engineering teams, Optimize data infrastructure", "teamCollaboration" : "Cross-functional teams; Engineering teams", "domainKnowledge" : "Recommendation systems", "domainList" : [ "recommendation-systems" ], "domainSpecificKnowledge" : [ "Recommendation systems" ], "toolProficiency" : [ "SQL", "Python", "R", "Scala", "Spark", "Dbt", "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy", "Snowflake", "BigQuery", "Redshift", "Databricks", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow", "AWS", "GCP", "Azure" ], "qualificationsBasic" : "SQL proficiency, Python proficiency", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification, Experience with scikit-learn, Experience with TensorFlow, Experience with PyTorch, Experience with XGBoost, Experience with LightGBM, Experience with Hugging Face, Experience with MLflow, Experience with Snowflake, Experience with BigQuery, Experience with Redshift, Experience with Databricks, Experience with dbt, Experience with Fivetran, Experience with Airflow, Experience with dbt Cloud, Experience with Delta Lake, Experience with AWS SageMaker, Experience with GCP Vertex AI, Experience with Azure ML Studio", "remoteFriendly" : false, "rawDescription" : "The opportunity Unity's Vector AI team builds the machine learning systems that decide which ads reach which players — across billions of monthly users on the world's leading game engine. Recommendation and ranking systems are the core of this work: predicting user value, optimizing bids, and delivering outcomes for advertisers at massive scale. We are building the next generation of these systems. The frontier has shifted — large language models, reinforcement learning from human feedback, and agentic AI are reshaping what recommendation systems can do. We are looking for PhD graduates who have worked at that frontier and want to bring those ideas into production systems that matter. What you'll be doing Design, build, and evaluate next-generation ranking and recommendation models that incorporate LLMs, RLHF, and preference learning to improve ad relevance and user experience. Develop user understanding systems — conversion prediction, behavioral modeling, and value estimation — that operate across billions of impressions. Apply reinforcement learning and optimization techniques to bidding strategy, auction dynamics, and real-time ad delivery. Design and run rigorous experiments using causal inference, A/B testing, and offline evaluation frameworks to measure and improve model quality. Partner with engineering to bring research ideas into production, working across the full pipeline from training data to deployed model. Communicate findings clearly to technical and non-technical stakeholders across engineering, product, and business teams. What we're looking for PhD in Computer Science, Machine Learning, Statistics, or a related field (graduating 2026 or recent graduate). Strong research foundations in one or more of: recommendation systems, reinforcement learning, LLM post-training or alignment, human-AI collaboration, probabilistic modeling, or optimization. Experience working with large-scale data and ML systems, whether through research or industry internships. Fluency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow. A track record of rigorous, high-quality research — publications at top venues (NeurIPS, ICML, ICLR, KDD, RecSys, ACL, WWW, or similar) are a strong signal. Strong written and verbal communication skills — able to make complex ideas accessible across technical and non-technical audiences. You might also have Industry experience in ads, recommendation, or user understanding systems (internship experience counts). Hands-on experience with production ML pipelines — training at scale, feature engineering, or experimentation infrastructure. Experience applying LLMs or generative models to ranking, retrieval, or structured prediction problems. Familiarity with agentic AI approaches — multi-step reasoning, tool use, or human-AI collaboration frameworks. Exposure to causal inference, uplift modeling, or A/B testing at scale. Genuine curiosity about applied research and the drive to see ideas through to impact. Additional information Relocation support is not available for this position Benefits At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance. Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status. While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program Life at Unity Unity [NYSE: U] is the world’s leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D — closing the gap between ideas and reality. For more information, please visit www.unity.com. Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know. This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English. Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity. Your privacy is important to us. Please take a moment to review our Prospect Privacy Policy and Applicant Privacy Policy. Should you have any concerns about your privacy, please contact us at DPO@unity.com. #MID #LI-ED1 *Note: This range reflects the anticipated base salary for this position. Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount will depend on several factors, including geographic location and the candidate’s relevant experience, professional background, and skill set. Gross pay salary $112,700—$169,100 USD", "summaryDescription" : "Machine Learning Engineer, Next-Generation Recommendation Systems (New Grad / PhD) at Unity Technologies. Skills: Data science, Machine learning, Data engineering. Develop and deploy machine learning models. Build and maintain data pipelines", "postedDate" : "2026-06-16T01:21:03.139", "createdAt" : "2026-06-16T01:21:03.139", "lastUpdated" : "2026-06-16T11:01:28.921", "ingestTimestamp" : "2026-06-16T01:21:03.139", "mongoId" : "6a30876cf292fd229c088d54", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 112700, "salaryAnnualMax" : 169100, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference", "Data science", "Machine learning", "Data engineering", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Statistical modeling", "Recommendation systems", "GCP Professional Data Engineer certification", "AWS Data Analytics certification", "Databricks Certified certification", "Dbt Certified certification", "SQL", "Python", "R", "Scala", "Spark", "Dbt", "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy", "Snowflake", "BigQuery", "Redshift", "Databricks", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow", "AWS", "GCP", "Azure" ], "skillCount" : 54, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 1.0, "_score" : 464.71207, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6ace74d8ee00a090e180", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T09:32:32.163", "fingerprint" : "b4ffce9ab73c45c5f7e7b329bbda1b5a72a15b6ea6498cf919a02080679e0dad", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4266740009", "externalId" : "4266740009", "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", "Quantitative Analysis", "Business Intelligence", "Data Science", "Analytics Engineering" ], "hardSkillsList" : [ "Data Labeling", "Content Evaluation", "Data Transformation", "Data Gathering", "Data Compilation", "Text Summarization", "Translation", "Content Generation" ], "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" }, { "name" : "Text Summarization", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" }, { "name" : "Content Generation", "level" : "intermediate" } ], "majorSkills" : "Generative AI, Large Language Models, AI Model Evaluation", "majorSkillsList" : [ "Generative AI", "Large Language Models", "AI Model Evaluation" ], "coreResponsibilities" : "Rate AI model performance, Label content elements, Assign categories or labels, Evaluate content quality, Generate labels for concepts, Create training data, Apply data transformations, Review data for functionality, Label model outputs, Order or rank items, Create prompts for AI, Evaluate content relevance, Generate AI responses, Rewrite existing text, Produce text summaries, Convert audio to text, Translate languages, Gather data for AI models, Compile digital content", "domainKnowledge" : "Artificial Intelligence; AI Systems", "domainList" : [ "artificial-intelligence", "ai-systems" ], "domainSpecificKnowledge" : [ "Artificial Intelligence", "AI Systems" ], "qualificationsBasic" : "Bachelor's degree in humanities, Professional C1/C2 English proficiency", "qualificationsPreferred" : "Advanced degrees 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, Large Language Models, AI Model Evaluation. Rate AI model performance. Label content elements", "postedDate" : "2026-06-14T08:37:32.160", "createdAt" : "2026-06-14T08:37:32.160", "lastUpdated" : "2026-06-15T09:32:32.163", "ingestTimestamp" : "2026-06-14T08:37:32.160", "mongoId" : "6a2c6ace74d8ee00a090e180", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data Labeling", "Content Evaluation", "Data Transformation", "Data Gathering", "Data Compilation", "Text Summarization", "Translation", "Content Generation", "Generative AI", "Large Language Models", "AI Model Evaluation", "Data Engineering", "Quantitative Analysis", "Business Intelligence", "Data Science", "Analytics Engineering", "Artificial Intelligence", "AI Systems" ], "skillCount" : 18, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 464.5556, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e183", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T09:29:44.122", "fingerprint" : "156aa427fa7acfbe2a1fde36ca5f8dfd6f70c1742601631f9c764919a99958d1", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4248761009", "externalId" : "4248761009", "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", "Quantitative Analysis", "AI Development" ], "hardSkillsList" : [ "Data Labeling", "Content Evaluation", "Data Transformation", "Text Summarization", "Translation", "Data Gathering" ], "hardSkills" : [ { "name" : "Data Labeling", "level" : "intermediate" }, { "name" : "Content Evaluation", "level" : "intermediate" }, { "name" : "Data Transformation", "level" : "intermediate" }, { "name" : "Text Summarization", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" }, { "name" : "Data Gathering", "level" : "intermediate" } ], "majorSkills" : "Generative AI, Large Language Models, AI Development", "majorSkillsList" : [ "Generative AI", "Large Language Models", "AI Development" ], "coreResponsibilities" : "Rate AI model performance, Label content elements, Assign categories or labels, Evaluate content quality, Generate labels for concepts, Create training data, Apply data transformations, Review data for functionality, Label model outputs, Identify content types, Order or rank items, Create prompts for AI, Evaluate content relevance, Generate AI responses, Rewrite existing text, Produce text summaries, Convert audio to text, Translate languages, Gather data for AI models", "domainKnowledge" : "Artificial Intelligence; Large Language Models", "domainList" : [ "artificial-intelligence", "large-language-models" ], "domainSpecificKnowledge" : [ "Artificial Intelligence", "Large Language Models" ], "qualificationsBasic" : "Bachelor's degree in humanities, Professional English proficiency, Expert English proficiency", "qualificationsPreferred" : "Advanced degrees preferred, Master's degree preferred, 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, Large Language Models, AI Development. Rate AI model performance. Label content elements", "postedDate" : "2026-06-14T08:09:59.464", "createdAt" : "2026-06-14T08:09:59.464", "lastUpdated" : "2026-06-15T09:29:44.122", "ingestTimestamp" : "2026-06-14T08:09:59.464", "mongoId" : "6a2c6ace74d8ee00a090e183", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data Labeling", "Content Evaluation", "Data Transformation", "Text Summarization", "Translation", "Data Gathering", "Generative AI", "Large Language Models", "AI Development", "Data Engineering", "Quantitative Analysis", "Artificial Intelligence" ], "skillCount" : 12, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 463.63583, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e191", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T09:44:46.976", "fingerprint" : "a8f34e5c0e6a83fa2974f0060a4f8ae131d5343a41fb4d4c2ac0cf7e37db3f6e", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4266675009", "externalId" : "4266675009", "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" ], "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Data compilation", "Text summarization", "Translation" ], "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" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Translation", "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 categories or labels, Evaluate content quality, Generate labels for concepts, Create training data, Review data for feature functionality, Label model outputs, Order or rank items, Create prompts for AI, Evaluate content relevance, Generate AI responses, Rewrite existing text, Produce text summaries, Convert audio to text, Translate languages, Gather data for AI models", "domainKnowledge" : "Artificial Intelligence; Large Language Models", "domainList" : [ "artificial-intelligence", "large-language-models" ], "domainSpecificKnowledge" : [ "Artificial Intelligence", "Large Language Models" ], "qualificationsBasic" : "Bachelor's degree in humanities, Professional English proficiency (C1/C2)", "qualificationsPreferred" : "Advanced degrees 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, LLM development, Data annotation. Rate AI model performance. Label content elements", "postedDate" : "2026-06-14T07:58:09.515", "createdAt" : "2026-06-14T07:58:09.515", "lastUpdated" : "2026-06-15T09:44:46.976", "ingestTimestamp" : "2026-06-14T07:58:09.515", "mongoId" : "6a2c6ace74d8ee00a090e191", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Data compilation", "Text summarization", "Translation", "Generative AI", "LLM development", "Data annotation", "Data Engineering", "Artificial Intelligence", "Large Language Models" ], "skillCount" : 13, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 462.3267, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e196", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T05:05:26.790", "fingerprint" : "1c562bb3eed7b5f1209f75c3327192284bac9a137150c835a862d6fc5a091cdf", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4248760009", "externalId" : "4248760009", "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", "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Text summarization", "Translation" ], "hardSkills" : [ { "name" : "Data labeling", "level" : "intermediate" }, { "name" : "Content evaluation", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Translation", "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 categories or labels, Evaluate content quality, Generate labels for concepts, Create training data, Apply data transformations, Review data for features, Label model outputs, Order or rank items, Create prompts for AI, Evaluate content relevance, Generate AI responses, Rewrite existing text, Produce text summaries, Convert audio to text, Translate languages, 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 in humanities, Professional English proficiency (C1/C2)", "qualificationsPreferred" : "Advanced degrees 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, LLM development, Data annotation. Rate AI model performance. Label content elements", "postedDate" : "2026-06-14T07:52:23.236", "createdAt" : "2026-06-14T07:52:23.236", "lastUpdated" : "2026-06-15T05:05:26.790", "ingestTimestamp" : "2026-06-14T07:52:23.236", "mongoId" : "6a2c6ace74d8ee00a090e196", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Text summarization", "Translation", "Generative AI", "LLM development", "Data annotation", "Artificial Intelligence", "Large Language Models" ], "skillCount" : 11, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 462.07117, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e174", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T09:21:40.415", "fingerprint" : "2d85f4eac0de4f697e556ff253b343e4dca49f3ffce9bc56d85ce4739cd55e3c", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4248692009", "externalId" : "4248692009", "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", "Quantitative Analysis", "AI Development" ], "hardSkillsList" : [ "Data Labeling", "Content Evaluation", "Data Transformation", "Text Summarization", "Translation", "Data Gathering" ], "hardSkills" : [ { "name" : "Data Labeling", "level" : "intermediate" }, { "name" : "Content Evaluation", "level" : "intermediate" }, { "name" : "Data Transformation", "level" : "intermediate" }, { "name" : "Text Summarization", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" }, { "name" : "Data Gathering", "level" : "intermediate" } ], "majorSkills" : "Generative AI, LLM Development, AI Model Evaluation", "majorSkillsList" : [ "Generative AI", "LLM Development", "AI Model Evaluation" ], "coreResponsibilities" : "Rate AI model performance, Label content elements, Assign categories or labels, Evaluate content quality, Generate labels for concepts, Create training data, Review data for functionality, Label model outputs, Order or rank items, Create prompts for AI, Evaluate content relevance, Generate AI responses, Rewrite existing text, Produce text summaries, Convert audio to text, Translate languages, Gather data for AI models", "domainKnowledge" : "Artificial Intelligence; Large Language Models", "domainList" : [ "artificial-intelligence", "large-language-models" ], "domainSpecificKnowledge" : [ "Artificial Intelligence", "Large Language Models" ], "qualificationsBasic" : "Bachelor's degree in humanities, Professional English proficiency (C1/C2)", "qualificationsPreferred" : "Advanced degrees 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, LLM Development, AI Model Evaluation. Rate AI model performance. Label content elements", "postedDate" : "2026-06-14T05:12:55.484", "createdAt" : "2026-06-14T05:12:55.484", "lastUpdated" : "2026-06-15T09:21:40.415", "ingestTimestamp" : "2026-06-14T05:12:55.484", "mongoId" : "6a2c6ace74d8ee00a090e174", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data Labeling", "Content Evaluation", "Data Transformation", "Text Summarization", "Translation", "Data Gathering", "Generative AI", "LLM Development", "AI Model Evaluation", "Data Engineering", "Quantitative Analysis", "AI Development", "Artificial Intelligence", "Large Language Models" ], "skillCount" : 14, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 455.7957, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a305119f292fd229cef9c97", "title" : "Lead Product Manager, Data and AI", "industry" : "Product", "salary" : { "min" : 85000.0, "max" : 130000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Lead Product Manager, Data and AI in Bulgaria, adjusted for SaaS industry and remote work." }, "location" : "US", "locations" : [ "US" ], "timestamp" : "2026-06-16T13:00:21.262", "fingerprint" : "82fe4f4fdc8ab1372055aa6158ae911736d6dc6afa73b5b74d4c6341bc3b8381", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/jobgether/f4b9f71e-4327-4077-a695-5a7cf7ad3271/apply", "externalId" : "f4b9f71e-4327-4077-a695-5a7cf7ad3271", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Bulgaria", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "Bulgaria", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 8, "experienceMaxYears" : 15, "experienceLevel" : "Lead", "technicalSkills" : "Machine learning, Generative AI, Large language models, LLMs, Advanced analytics", "professionalSkills" : [ "Product strategy", "Roadmap development", "Product lifecycle management", "Stakeholder management", "Product requirements", "Data-driven decision making" ], "hardSkillsList" : [ "AI development", "Analytics solutions", "Product performance measurement", "Experimentation frameworks" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "AI development", "level" : "intermediate" }, { "name" : "Analytics solutions", "level" : "intermediate" }, { "name" : "Product performance measurement", "level" : "intermediate" }, { "name" : "Experimentation frameworks", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Machine learning, Generative AI, Analytics solutions", "majorSkillsList" : [ "Machine learning", "Generative AI", "Analytics solutions" ], "coreResponsibilities" : "Define product vision and roadmap, Execute product vision and roadmap, Align initiatives with business objectives, Lead development of AI solutions, Lead deployment of AI solutions, Manage product lifecycle, Collaborate with cross-functional stakeholders, Integrate intelligent capabilities into products, Establish frameworks for measuring product performance, Establish frameworks for experimentation, Establish frameworks for business impact, Use data-driven insights for decision-making, Use data-driven insights for optimization, Translate business challenges into product requirements, Act as bridge between technical and non-technical stakeholders, Promote responsible AI development, Partner with governance stakeholders, Partner with privacy stakeholders, Partner with compliance stakeholders, Ensure ethical product outcomes, Ensure secure product outcomes, Ensure reliable product outcomes, Mentor team members, Contribute to product management best practices, Foster culture of innovation, Foster culture of collaboration, Foster culture of continuous improvement", "teamCollaboration" : "Cross-functional stakeholders; Product teams; Engineering teams; Design teams; Operations teams; Business teams; Multidisciplinary teams", "projectManagementSkills" : [ "Roadmap development", "Prioritization", "Execution" ], "domainKnowledge" : "Machine learning concepts; Generative AI technologies; Large language models; LLMs; Advanced analytics; AI infrastructure; Data privacy; Data governance; AI security; Ethical AI principles", "domainList" : [ "machine-learning-concepts", "generative-ai-technologies", "large-language-models", "llms", "advanced-analytics", "ai-infrastructure", "data-privacy", "data-governance", "ai-security", "ethical-ai-principles" ], "domainSpecificKnowledge" : [ "Machine learning concepts", "Generative AI technologies", "Large language models", "LLMs", "Advanced analytics", "AI infrastructure", "Data privacy", "Data governance", "AI security", "Ethical AI principles" ], "communicationSkills" : "Explain technical concepts; Explain trade-offs", "continuousLearning" : "Product management best practices", "innovationCreativity" : "Culture of innovation", "problemSolvingSkills" : "Navigate ambiguity; Prioritize competing objectives; Execute complex initiatives", "qualificationsBasic" : "Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative discipline, 8+ years of product management experience within enterprise SaaS, cloud software, technology, or highly regulated industries, At least 3 years of hands-on experience launching and scaling machine learning, AI, or data-driven products, Deep understanding of machine learning concepts, generative AI technologies, large language models (LLMs), advanced analytics, and the infrastructure required to support AI solutions, Proven ability to develop product strategies, navigate ambiguity, prioritize competing objectives, and successfully execute complex initiatives, Experience working across multidisciplinary teams in fast-paced environments", "qualificationsPreferred" : "Familiarity with regulated industries, Understanding of data privacy, governance, security, and ethical AI principles", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "## Accountabilities Define and execute a multi-year product vision and roadmap for data and AI platforms, aligning initiatives with business objectives, growth strategies, and operational priorities. Lead the development and deployment of advanced AI, machine learning, generative AI, and analytics solutions, managing the full product lifecycle from ideation and experimentation to scalable production delivery. Collaborate closely with cross-functional stakeholders across product, engineering, design, operations, and business teams to integrate intelligent capabilities into core products and workflows. Establish frameworks for measuring product performance, experimentation, and business impact, using data-driven insights to guide decision-making and optimization efforts. Translate complex business challenges into clear product requirements and act as a bridge between technical specialists and non-technical stakeholders. Promote responsible AI development by partnering with governance, privacy, and compliance stakeholders to ensure ethical, secure, and reliable product outcomes. Mentor team members, contribute to product management best practices, and help foster a culture of innovation, collaboration, and continuous improvement. Requirements Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative discipline. 8+ years of product management experience within enterprise SaaS, cloud software, technology, or highly regulated industries, with a strong track record of delivering large-scale products. At least 3 years of hands-on experience launching and scaling machine learning, AI, or data-driven products. Deep understanding of machine learning concepts, generative AI technologies, large language models (LLMs), advanced analytics, and the infrastructure required to support AI solutions. Proven ability to develop product strategies, navigate ambiguity, prioritize competing objectives, and successfully execute complex initiatives. Strong communication and stakeholder management skills, with the ability to explain technical concepts and trade-offs to executive and non-technical audiences. Experience working across multidisciplinary teams in fast-paced environments and influencing decisions without direct authority. Familiarity with regulated industries and an understanding of data privacy, governance, security, and ethical AI principles is considered a strong advantage. Benefits Annual base salary ranging from $161,000 to $221,500, depending on experience, qualifications, and location. Eligibility for performance-based or discretionary bonus programs. Comprehensive healthcare coverage, including medical, dental, vision, life, and disability insurance options. Flexible spending accounts (FSA) and health savings account (HSA) programs. Access to coaching, therapy, and well-being support services. Equity participation through company stock programs. Generous paid time off, including vacation, sick leave, and company holidays. Paid parental leave. 401(k) retirement plan with company matching contributions. Monthly technology allowance. Additional wellness initiatives, employee events, recognition programs, and community-focused activities. ## Additional Information How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1", "summaryDescription" : "Lead Product Manager, Data and AI. Skills: Machine learning, Generative AI, Analytics solutions. Define product vision and roadmap. Execute product vision and roadmap", "postedDate" : "2026-06-15T09:26:38.520", "createdAt" : "2026-06-15T09:26:38.520", "lastUpdated" : "2026-06-16T13:00:21.262", "ingestTimestamp" : "2026-06-16T03:24:32.331", "mongoId" : "6a305119f292fd229cef9c97", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ "AI development", "Analytics solutions", "Product performance measurement", "Experimentation frameworks", "Leadership", "Mentoring", "Machine learning", "Generative AI", "Product strategy", "Roadmap development", "Product lifecycle management", "Stakeholder management", "Product requirements", "Data-driven decision making", "Prioritization", "Execution", "Machine learning concepts", "Generative AI technologies", "Large language models", "LLMs", "Advanced analytics", "AI infrastructure", "Data privacy", "Data governance", "AI security", "Ethical AI principles" ], "skillCount" : 26, "jobCategory" : "product", "jobSubcategory" : "product_management", "seniorityLevel" : "Lead", "dataQualityScore" : 0.8888889, "_score" : 455.69116, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "SaaS", "llmIndustryConfidence" : 0.98 }, { "id" : "6a307f6cf292fd229c059136", "title" : "Senior Software Engineer, Recommendations, Search Intelligence", "industry" : "Technology", "salary" : { "min" : 175000.0, "max" : 250000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Software Engineer in Mountain View, CA, adjusted for the technology industry and senior experience level." }, "location" : "[Mountain View, CA, USA, [100 Bay Vw Dr, Mountain View, CA 94043, USA], Mountain View, 94043, CA, US]", "locations" : [ "[Mountain View, CA, USA, [100 Bay Vw Dr, Mountain View, CA 94043, USA], Mountain View, 94043, CA, US]" ], "timestamp" : "2026-06-16T12:39:28.595", "fingerprint" : "479daf96f3cf2c929c7116bc2d6b1b647aa95e7c43996dce6f491b5ee3434f76", "source" : "google", "language" : "en", "externalId" : "115920673452237510", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Mountain View", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.3893889,-122.0832101" } ], "locationText" : "Mountain View, California, United States", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "summaryDescription" : "Senior Software Engineer, Recommendations, Search Intelligence", "postedDate" : "2026-06-16T01:52:13.924", "createdAt" : "2026-06-16T01:52:13.924", "lastUpdated" : "2026-06-16T12:39:28.595", "ingestTimestamp" : "2026-06-16T01:52:13.924", "mongoId" : "6a307f6cf292fd229c059136", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 175000, "salaryAnnualMax" : 250000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.5555556, "_score" : 455.6911, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6ace74d8ee00a090e1ab", "title" : "Generative AI Specialist", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 52000.0, "max" : 78000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an Entry-level Generative AI Specialist in the US Technology industry, adjusted for remote work and part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T05:00:05.477", "fingerprint" : "5a1c6bd553651eabdd68aa611f0efb6dba0c5d37c1f36bec0187d66357f914c8", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4282642009", "externalId" : "4282642009", "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 models, AI systems, AI development", "professionalSkills" : [ "Data engineering", "Quantitative analysis", "Business intelligence", "Analytics engineering", "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills" ], "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Data compilation", "Text summarization", "Language translation", "Prompt creation", "Content generation" ], "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" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Language translation", "level" : "intermediate" }, { "name" : "Prompt creation", "level" : "intermediate" }, { "name" : "Content generation", "level" : "intermediate" } ], "majorSkills" : "Generative AI, Large language models, AI development, Data evaluation", "majorSkillsList" : [ "Generative AI", "Large language models", "AI development", "Data evaluation" ], "coreResponsibilities" : "Rate AI models, Assess AI algorithms, Label content elements, Assign predefined categories, Evaluate content quality, Generate labels, Create training data, Apply data transformations, Modify images, Generate new text, Alter audio/video signals, Review data, Identify product feature functionality, Label model outputs, Order or rank items, Create prompts, Generate responses, Rewrite existing text, Produce concise summaries, Convert spoken language, Translate text, Gather data, Compile data", "domainKnowledge" : "Generative AI; Large language models; AI systems; AI development; Data engineering", "domainList" : [ "generative-ai", "large-language-models", "ai-systems", "ai-development", "data-engineering" ], "domainSpecificKnowledge" : [ "Generative AI", "Large language models", "AI systems", "AI development", "Data engineering" ], "innovationCreativity" : "Shape the future of AI", "problemSolvingSkills" : "Reasoning", "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 a 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" : "Generative AI Specialist at Innodata Inc.. Skills: Generative AI, Large language models, AI development, Data evaluation. Rate AI models. Assess AI algorithms", "postedDate" : "2026-06-14T04:12:39.002", "createdAt" : "2026-06-14T04:12:39.002", "lastUpdated" : "2026-06-15T05:00:05.477", "ingestTimestamp" : "2026-06-14T04:12:39.002", "mongoId" : "6a2c6ace74d8ee00a090e1ab", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 52000, "salaryAnnualMax" : 78000, "salaryBand" : "50k-75k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Data compilation", "Text summarization", "Language translation", "Prompt creation", "Content generation", "Generative AI", "Large language models", "AI development", "Data evaluation", "Data engineering", "Quantitative analysis", "Business intelligence", "Analytics engineering", "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "AI systems" ], "skillCount" : 23, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 453.5841, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e16d", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T11:40:57.683", "fingerprint" : "5d2455df9ba4f1b3351c4d6d2f8483c7c76493157f715e19b70325d8029ea3bd", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4248770009", "externalId" : "4248770009", "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" : [ "Content labeling", "Data transformation", "Content evaluation", "Text summarization", "Language translation", "Data gathering", "Data compilation" ], "hardSkills" : [ { "name" : "Content labeling", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Content evaluation", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Language translation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" }, { "name" : "Data compilation", "level" : "intermediate" } ], "majorSkills" : "Generative AI, LLM development, AI model evaluation", "majorSkillsList" : [ "Generative AI", "LLM development", "AI model evaluation" ], "coreResponsibilities" : "Rate AI model performance, Label content elements, Assign categories or labels, Evaluate content quality, Generate labels for concepts, Create training data, Apply data transformations, Review data for feature functionality, Label model outputs, Order or rank items, Create prompts for AI, Evaluate content relevance, Generate AI responses, Rewrite existing text, Produce text summaries, Convert audio to text, Translate languages, Gather data for AI models, Compile digital content", "domainKnowledge" : "Generative AI; Large Language Models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large Language Models" ], "qualificationsBasic" : "Bachelor's degree in humanities, Professional English proficiency (C1/C2)", "qualificationsPreferred" : "Advanced degrees (Master's or PhD), Expert English proficiency (C2)", "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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, LLM development, AI model evaluation. Rate AI model performance. Label content elements", "postedDate" : "2026-06-14T04:07:43.738", "createdAt" : "2026-06-14T04:07:43.738", "lastUpdated" : "2026-06-15T11:40:57.683", "ingestTimestamp" : "2026-06-14T04:07:43.738", "mongoId" : "6a2c6ace74d8ee00a090e16d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Content labeling", "Data transformation", "Content evaluation", "Text summarization", "Language translation", "Data gathering", "Data compilation", "Generative AI", "LLM development", "AI model evaluation", "Data Engineering", "AI Development", "Large Language Models" ], "skillCount" : 13, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 452.91742, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e1ad", "title" : "Generative AI Specialist", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 45000.0, "max" : 75000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an Entry-level Generative AI Specialist in the US Technology industry, adjusted for remote work and part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T04:48:55.369", "fingerprint" : "a24844adc37de01968dc6dd7f5cad4840f34a1e71c67ec1a32ba79e4f95f33f1", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4266725009", "externalId" : "4266725009", "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", "hardSkillsList" : [ "Data labeling", "Data transformation", "Content evaluation", "Prompt creation", "Text summarization", "Language translation", "Data gathering" ], "hardSkills" : [ { "name" : "Data labeling", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Content evaluation", "level" : "intermediate" }, { "name" : "Prompt creation", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Language translation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" } ], "majorSkills" : "Generative AI, LLMs, Data labeling", "majorSkillsList" : [ "Generative AI", "LLMs", "Data labeling" ], "coreResponsibilities" : "Rate AI models, Assess AI algorithms, Label content elements, Assign predefined categories, Evaluate content quality, Generate labels, Create training data, Apply data transformations, Modify images, Generate new text, Alter audio/video, Review data, Identify product features, Label model outputs, Order or rank items, Create prompts, Evaluate content relevance, Generate responses, Rewrite existing text, Produce concise summaries, Convert audio to text, Translate languages, Gather data", "domainKnowledge" : "Generative AI; Large Language Models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large Language Models" ], "qualificationsBasic" : "Bachelor's degree humanities, Professional C1/C2 English", "qualificationsPreferred" : "Advanced degrees 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" : "Generative AI Specialist at Innodata Inc.. Skills: Generative AI, LLMs, Data labeling. Rate AI models. Assess AI algorithms", "postedDate" : "2026-06-14T03:18:33.445", "createdAt" : "2026-06-14T03:18:33.445", "lastUpdated" : "2026-06-15T04:48:55.369", "ingestTimestamp" : "2026-06-14T03:18:33.445", "mongoId" : "6a2c6ace74d8ee00a090e1ad", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 45000, "salaryAnnualMax" : 75000, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Data transformation", "Content evaluation", "Prompt creation", "Text summarization", "Language translation", "Data gathering", "Generative AI", "LLMs", "Large Language Models" ], "skillCount" : 10, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 451.6671, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e165", "title" : "Generative 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 Generative AI Annotator in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T13:05:49.125", "fingerprint" : "f3e3bf60d2ecf78e8f14b4d52e38f18d3cdd8c18696b26a42bfeb3df6fd2534a", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4234813009", "externalId" : "4234813009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "PART_TIME", "minimumEducation" : "High School", "technicalSkills" : "Generative AI, Large language models, Machine learning models, AI algorithms, Machine learning", "professionalSkills" : [ "Data engineering", "Evaluation frameworks", "Human expertise", "Data quality", "Outcome delivery" ], "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Data review", "Data ordering", "Prompt creation", "Content relevance", "Response generation", "Text rewriting", "Summarization", "Transcription", "Translation", "Data gathering", "Data compilation" ], "hardSkills" : [ { "name" : "Data labeling", "level" : "intermediate" }, { "name" : "Content evaluation", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Data review", "level" : "intermediate" }, { "name" : "Data ordering", "level" : "intermediate" }, { "name" : "Prompt creation", "level" : "intermediate" }, { "name" : "Content relevance", "level" : "intermediate" }, { "name" : "Response generation", "level" : "intermediate" }, { "name" : "Text rewriting", "level" : "intermediate" }, { "name" : "Summarization", "level" : "intermediate" }, { "name" : "Transcription", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" }, { "name" : "Data compilation", "level" : "intermediate" } ], "majorSkills" : "Generative AI, LLM annotation, Data labeling", "majorSkillsList" : [ "Generative AI", "LLM annotation", "Data labeling" ], "coreResponsibilities" : "Rate AI model performance, Assess AI algorithm performance, 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, Generate responses, Rewrite existing text, Preserve original meaning, Produce concise summaries, Convert audio to text, Convert text to another language, 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" ], "outcomesObjectives" : "Build AI systems at scale; Deliver highest quality data; Deliver outstanding outcomes", "qualificationsBasic" : "High School Diploma or higher, Professional or Expert level proficiency (C1/C2) 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 Generative AI 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 $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" : "Generative AI Annotator at Innodata Inc.. Skills: Generative AI, LLM annotation, Data labeling. Rate AI model performance. Assess AI algorithm performance", "postedDate" : "2026-06-14T03:34:55.088", "createdAt" : "2026-06-14T03:34:55.088", "lastUpdated" : "2026-06-15T13:05:49.125", "ingestTimestamp" : "2026-06-14T03:34:55.088", "mongoId" : "6a2c6ace74d8ee00a090e165", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 31000, "salaryAnnualMax" : 45000, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Data review", "Data ordering", "Prompt creation", "Content relevance", "Response generation", "Text rewriting", "Summarization", "Transcription", "Translation", "Data gathering", "Data compilation", "Generative AI", "LLM annotation", "Data engineering", "Evaluation frameworks", "Human expertise", "Data quality", "Outcome delivery", "Large language models", "AI systems" ], "skillCount" : 23, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 451.47076, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6ace74d8ee00a090e1a1", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T07:54:53.344", "fingerprint" : "f46a43d4db7d147b8adfc42c756f4fccd9b42ea2db724843f3d2fa5db3a7c6a1", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4248723009", "externalId" : "4248723009", "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", "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Text summarization", "Translation" ], "hardSkills" : [ { "name" : "Data labeling", "level" : "intermediate" }, { "name" : "Content evaluation", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Translation", "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 categories or labels, Evaluate content quality, Generate labels for concepts, Create training data, Apply data transformations, Review data for functionality, Label model outputs, Identify content types, Order or rank items, Create prompts for AI, Evaluate content relevance, Generate AI responses, Rewrite existing text, Produce text summaries, Convert audio to text, Translate languages, Gather data for AI models", "domainKnowledge" : "Artificial Intelligence; Large Language Models", "domainList" : [ "artificial-intelligence", "large-language-models" ], "domainSpecificKnowledge" : [ "Artificial Intelligence", "Large Language Models" ], "qualificationsBasic" : "Bachelor's degree in humanities, Professional English proficiency (C1/C2)", "qualificationsPreferred" : "Advanced degrees 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, LLM development, Data annotation. Rate AI model performance. Label content elements", "postedDate" : "2026-06-14T03:38:41.846", "createdAt" : "2026-06-14T03:38:41.846", "lastUpdated" : "2026-06-15T07:54:53.344", "ingestTimestamp" : "2026-06-14T03:38:41.846", "mongoId" : "6a2c6ace74d8ee00a090e1a1", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Text summarization", "Translation", "Generative AI", "LLM development", "Data annotation", "Artificial Intelligence", "Large Language Models" ], "skillCount" : 11, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 450.8725, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e16f", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T08:59:50.244", "fingerprint" : "5e65c36e692059ae47179f02f95d2a7efc8f97569b3d9c7880af85393a1ac222", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4248773009", "externalId" : "4248773009", "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", "hardSkillsList" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Text summarization", "Translation" ], "hardSkills" : [ { "name" : "Data labeling", "level" : "intermediate" }, { "name" : "Content evaluation", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Data gathering", "level" : "intermediate" }, { "name" : "Text summarization", "level" : "intermediate" }, { "name" : "Translation", "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 categories or labels, Evaluate content quality, Generate labels for concepts, Create training data, Apply data transformations, Review data for functionality, Label model outputs, Identify content types, Order or rank items, Create prompts for AI, Evaluate content relevance, Generate AI responses, Rewrite existing text, Produce text summaries, Convert audio to text, Translate languages, Gather data for AI models", "domainKnowledge" : "Artificial Intelligence; Large Language Models", "domainList" : [ "artificial-intelligence", "large-language-models" ], "domainSpecificKnowledge" : [ "Artificial Intelligence", "Large Language Models" ], "qualificationsBasic" : "Bachelor's degree in humanities, Professional English proficiency (C1/C2)", "qualificationsPreferred" : "Advanced degrees 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, LLM development, Data annotation. Rate AI model performance. Label content elements", "postedDate" : "2026-06-14T03:21:28.270", "createdAt" : "2026-06-14T03:21:28.270", "lastUpdated" : "2026-06-15T08:59:50.244", "ingestTimestamp" : "2026-06-14T03:21:28.270", "mongoId" : "6a2c6ace74d8ee00a090e16f", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data labeling", "Content evaluation", "Data transformation", "Data gathering", "Text summarization", "Translation", "Generative AI", "LLM development", "Data annotation", "Artificial Intelligence", "Large Language Models" ], "skillCount" : 11, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 450.11472, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e18c", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T04:52:57.557", "fingerprint" : "171685893717cdf720e533007a89d10046ac9b9946ca235a90fda3dfa36f995a", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4266654009", "externalId" : "4266654009", "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" ], "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" } ], "majorSkills" : "Generative AI, LLM Development, Data Annotation", "majorSkillsList" : [ "Generative AI", "LLM Development", "Data Annotation" ], "coreResponsibilities" : "Rate AI model performance, Label content elements, Assign categories or labels, Evaluate content quality, Generate labels for concepts, Create training data, Review data for feature functionality, Label model outputs, Order or rank items, Create prompts for AI systems, Evaluate content relevance, Generate AI responses, Rewrite existing text, Produce text summaries, Convert audio to text, Translate languages, 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 in humanities, Professional English proficiency (C1/C2)", "qualificationsPreferred" : "Advanced degrees (Master's or PhD), Expert English proficiency (C2)", "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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, LLM Development, Data Annotation. Rate AI model performance. Label content elements", "postedDate" : "2026-06-14T02:56:18.938", "createdAt" : "2026-06-14T02:56:18.938", "lastUpdated" : "2026-06-15T04:52:57.557", "ingestTimestamp" : "2026-06-14T02:56:18.938", "mongoId" : "6a2c6ace74d8ee00a090e18c", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data Labeling", "Content Evaluation", "Data Transformation", "Prompt Creation", "Text Summarization", "Translation", "Data Gathering", "Generative AI", "LLM Development", "Data Annotation", "Data Engineering", "AI Development", "Artificial Intelligence", "Large Language Models" ], "skillCount" : 14, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 449.0088, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e17f", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T08:12:08.956", "fingerprint" : "72ba7864cc504c999723acd88652858f0ed2154b03b0d33d2898fb87cc78919f", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4266722009", "externalId" : "4266722009", "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", "Quantitative Analysis", "Business Intelligence", "Data Science", "Analytics Engineering" ], "hardSkillsList" : [ "Data Labeling", "Content Evaluation", "Data Transformation", "Data Gathering", "Data Compilation", "Prompt Creation", "Text Summarization", "Translation", "Data Augmentation" ], "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" }, { "name" : "Prompt Creation", "level" : "intermediate" }, { "name" : "Text Summarization", "level" : "intermediate" }, { "name" : "Translation", "level" : "intermediate" }, { "name" : "Data Augmentation", "level" : "intermediate" } ], "majorSkills" : "Generative AI, Large Language Models, AI Model Evaluation", "majorSkillsList" : [ "Generative AI", "Large Language Models", "AI Model Evaluation" ], "coreResponsibilities" : "Rate AI model performance, Label content elements, Assign predefined categories, Evaluate content quality, Generate labels for concepts, Create training data, Apply data transformations, Review data for product features, Label model outputs, Order or rank items, Create prompts for AI, Evaluate content relevance, Generate AI responses, Rewrite existing text, Produce text summaries, Convert audio to text, Translate languages, Gather data for AI, Compile digital content", "teamCollaboration" : "Global contributor community; Subject Matter Expert", "domainKnowledge" : "Artificial Intelligence; LLM development", "domainList" : [ "artificial-intelligence", "llm-development" ], "domainSpecificKnowledge" : [ "Artificial Intelligence", "LLM development" ], "qualificationsBasic" : "Bachelor's degree in humanities, Professional C1/C2 English proficiency", "qualificationsPreferred" : "Advanced degrees 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 a 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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, Large Language Models, AI Model Evaluation. Rate AI model performance. Label content elements", "postedDate" : "2026-06-14T02:44:54.358", "createdAt" : "2026-06-14T02:44:54.358", "lastUpdated" : "2026-06-15T08:12:08.956", "ingestTimestamp" : "2026-06-14T02:44:54.358", "mongoId" : "6a2c6ace74d8ee00a090e17f", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data Labeling", "Content Evaluation", "Data Transformation", "Data Gathering", "Data Compilation", "Prompt Creation", "Text Summarization", "Translation", "Data Augmentation", "Generative AI", "Large Language Models", "AI Model Evaluation", "Data Engineering", "Quantitative Analysis", "Business Intelligence", "Data Science", "Analytics Engineering", "Artificial Intelligence", "LLM development" ], "skillCount" : 19, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 448.97577, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e194", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 41600.0, "max" : 62400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US, adjusted for part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T10:55:34.830", "fingerprint" : "ffde85f86169fe4df1162e66b5c6f6f1d2a46dafe0e41936c57d046452b72ba8", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4266677009", "externalId" : "4266677009", "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" ], "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" } ], "majorSkills" : "Generative AI, LLM Development, Data Annotation", "majorSkillsList" : [ "Generative AI", "LLM Development", "Data Annotation" ], "coreResponsibilities" : "Rate AI model performance, Label content elements, Assign categories or labels, Evaluate content quality, Generate labels for concepts, Create training data, Review data for feature functionality, Label model outputs, Order or rank items, Create prompts for AI systems, Evaluate content relevance, Generate AI responses, Rewrite existing text, Produce text summaries, Convert audio to text, Translate languages, 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 in humanities, Professional English proficiency (C1/C2)", "qualificationsPreferred" : "Advanced degrees (Master's or PhD), Expert English proficiency (C2)", "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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, LLM Development, Data Annotation. Rate AI model performance. Label content elements", "postedDate" : "2026-06-14T02:43:46.447", "createdAt" : "2026-06-14T02:43:46.447", "lastUpdated" : "2026-06-15T10:55:34.830", "ingestTimestamp" : "2026-06-14T02:43:46.447", "mongoId" : "6a2c6ace74d8ee00a090e194", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 41600, "salaryAnnualMax" : 62400, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data Labeling", "Content Evaluation", "Data Transformation", "Prompt Creation", "Text Summarization", "Translation", "Generative AI", "LLM Development", "Data Annotation", "Data Engineering", "AI Development", "Artificial Intelligence", "Large Language Models" ], "skillCount" : 13, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 448.4577, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e190", "title" : "Generative AI Associate", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 31200.0, "max" : 52000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Generative AI Associate in the US Technology industry, adjusted for remote work and part-time employment." }, "location" : "ISL - Remote - US", "locations" : [ "ISL - Remote - US" ], "timestamp" : "2026-06-15T07:23:53.356", "fingerprint" : "0b44a3dd536f82007b9be9fa8d6004d8b66b5ec75baa4878fab51b0981f14c2e", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4266674009", "externalId" : "4266674009", "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" ], "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" } ], "majorSkills" : "Generative AI, LLM Development, Data Annotation", "majorSkillsList" : [ "Generative AI", "LLM Development", "Data Annotation" ], "coreResponsibilities" : "Rate AI model performance, Label content elements, Assign categories or labels, Evaluate content quality, Generate labels for concepts, Create training data, Review data for feature functionality, Label model outputs, Order or rank items, Create prompts for AI systems, Evaluate content relevance, Generate AI responses, Rewrite existing text, Produce text summaries, Convert audio to text, Translate languages, 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 in humanities, Professional English proficiency (C1/C2)", "qualificationsPreferred" : "Advanced degrees (Master's or PhD), Expert English proficiency (C2)", "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" : "Generative AI Associate at Innodata Inc.. Skills: Generative AI, LLM Development, Data Annotation. Rate AI model performance. 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Skills: Product strategy, Roadmap development, User stories, Cross-functional collaboration. Develop product strategy. 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