Cohere
Tech / AI / Software
DataAnnotationSpecialist,Japanese
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Annotation Specialist, Japanese at Cohere. Skills: Japanese Writing, Japanese Translation, Data Manipulation, Labeling, Ranking, Auditing, Correcting text output. Label and Rank machine learning data. Audit and Correct any inaccuracies in language data”
Industry & Context.
tackling problems in creative ways
This is a part-time independent contractor position, BYOD - Bring Your Own Device (laptop), 12 month contract, working with human generated and model generated tasks that may involve exposure to not safe for work (NSFW) text content as part of data annotation tasks, including explicit, offensive, or other inappropriate material.
What They're Looking For.
Must Have
Japanese Writing, Japanese Translation, Data Manipulation skill, Native or near-native proficiency in excellent command over English, Expert reading and writing skills, Basic familiarity with JSON/TSV/CSV/Markdown data manipulation, attention to detail and commitment to accuracy, High tolerance for repetitive and monotonous work, Ability to follow complex instructions, navigate ambiguity and work independently, Superb sense of urgency and time management, Curiosity about technology and a knack for tackling problems in creative ways, A reliable laptop
Nice to Have
Advanced proficiency in Chinese
What You'll Do.
Label and Rank machine learning data
Audit and Correct any inaccuracies in language data
Complete reading and text-based assignments
Evaluate and complete preference-based tasks
Identify and suggest opportunities for improving data quality and model performance
Provide feedback to cross-functional team members
Maintain meticulous attention to detail while performing repetitive and precise tasks
How You'll Work.
Team & Collaboration
Collaborate and communicate effectively, providing feedback to cross-functional team members, particularly on Japanese language-related matters.
Communication Scope
Collaborate and communicate effectively; providing feedback
Full Job Description
Who are we? Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers. Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products. Join us on our mission and shape the future! Why this role? We are on a mission to build machines that understand the world and make them safely accessible to all. Data quality is foundational to this process. Machines (or Large Language Models to be exact) learn in similar ways to humans - by way of feedback. By labelling, ranking, auditing, and correcting text output, you will improve Large Language Model’s performance for iterations to come, thus having a lasting impact on Cohere’s tech. Cohere seeks dynamic and dedicated Data Annotators with exceptional Japanese Writing, Translation, and Data Manipulation skill. Please Note: This is a part-time independent contractor position available within Canada. We seek candidates who are able to commit to 16 hours per week minimum at a 30 CAD/hour contract rate. This role is BYOD 💻 - Bring Your Own Device (laptop). Remote work within Canada. 12 month contract. Performance incentives included! As a Data Annotation Specialist, you will: - Label and Rank: Accurately label and rank machine learning data with advanced proficiency in Chinese, ensuring data integrity and quality. - Audit and Correct: Scrutinize an
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