Remote AI training and data labeling jobs

Annotate video captured by robotic systems (objects, movements, events), catch edge cases, and help the AI team refine annotation protocols and capture strategy. For people with hands-on computer vision and video annotation experience. 300 openings, remote contractor, $50–90/hour.

Review datasets and task outputs against rubrics and guidelines, flag errors and inconsistencies, and document your reasoning where the rules run out. US-based only. 30 openings, remote contractor, $30–60/hour, 3–5+ years in data quality, QA or analysis preferred.

Remote hourly contract for biostatisticians, epidemiologists and applied economists who already run Stata SE on their own Windows PC. $45–55/hour, paid weekly via Stripe or Wise. Your own Stata SE licence and a display above 2.5 megapixels are required. Tasks are not described.

Review large business datasets for accuracy and completeness under strict PII and privacy rules, flag quality problems and write findings that feed AI training. Remote contractor, $31–60/hour, 50 openings.

Pick information-rich charts from your field and write unambiguous, multi-step quantitative questions about them, with worked answers, to train AI on chart reasoning. Suits medicine, finance, engineering, earth science, data science and operations professionals with two years of chart-heavy work. 50 openings, $25–50/hour.

Run realistic analytics workflows through AI assistants connected to Snowflake, then check every figure they produce with your own SQL. You also maintain the seeded test data, warehouse roles and connector setups. Remote contractor, $50–60/hour, 4 openings, 3+ years of SQL and Snowflake preferred.

Data scientists from top tech, finance or research firms evaluate AI answers on statistics, ML and experimentation, and write expert prompts and reference solutions for a leading AI lab. Contractor, remote, 100 openings, $245–280/hour. English-speaking-country base preferred.

A full-time micro1 research role designing robotics datasets, collection methods, annotation schemas and evaluations for embodied AI (egocentric video, teleop, trajectories, simulation). Base salary $200,000–320,000 plus equity, remote, one opening. Two to five-plus years in robotics or applied ML.

ML systems engineers write and evaluate training tasks for a frontier lab across GPU kernels, performance profiling, distributed debugging and LLM inference serving, plus the rubrics that grade them. 2+ years of hands-on ML infrastructure work. Canada, UK or US; 40 hours a week. $90–120/hour.

Audit applied machine-learning tasks used to train and evaluate a frontier AI lab's models: experiment design, model selection, evaluation methodology, leakage and metric gaming. For US practitioners with 3+ years of hands-on experimental ML in PyTorch, TensorFlow, scikit-learn or XGBoost. $70–90/hour.

Clean messy real-world datasets, run descriptive and inferential analyses in Python or R, build clear visualisations and explain the results to non-technical readers, feeding AI model training data. MS or PhD in a quantitative field preferred. 50 openings, contractor, $60–120/hour.

Run realistic developer workflows (pull requests, code review, issues, CI runs) through AI tools and grade whether the results are correct, while seeding reproducible repos and wiring up integrations. Three years of Git and CI/CD experience; MCP and connector familiarity valued. Four openings, $50–70/hour.