Remote AI training and data labeling jobs

Grade AI-generated slides, spreadsheets and documents for real-world data science quality, flagging factual, visual and presentation errors in structured written feedback. Needs 5+ years at a top firm in the US, UK, Canada, Australia or New Zealand. $100–150/hour.

An expert-interview listing for engineers who have shipped production search, especially agentic search in the LLM era: a 25-minute conversational interview about relevance, evaluation and real trade-offs, with a possible paid 30-minute follow-up call at $200. No coding, no take-home. Listed at $80–150 per task.

Author executable scientific-computing problems in ecology, biochemistry and genetics for Sci Code, a new AI benchmark: source a paper, dataset or repo, write the prompt and grading criteria, and keep it only if frontier models mostly fail. PhD plus Python or R, Git and Docker. 6 weeks, 20+ hours a week, $70/hour.

A full-time research engineering role at micro1 building RL environments, reward functions, verifiers, synthetic data pipelines and automated evaluation systems. Base salary $200,000–300,000 plus equity and benefits, remote, one opening. Deep reinforcement learning experience required.

Write multi-step benchmark questions about hard data-science charts (Sankey diagrams, heatmaps, calibration curves, residual plots, correlation matrices) with unambiguous, fully worked answers for AI evaluation. Bachelor's or equivalent plus two years. 50 openings, contractor, $25–50/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.

Build, tune and evaluate ML models in Python with MongoDB-backed data pipelines for a customer AI training project, and document every experiment. Remote contractor, $80–140/hour, 35 openings. scikit-learn, TensorFlow or PyTorch plus hands-on MongoDB is the core stack.

Build, break and verify real machine learning engineering tasks: model components, reproducible training and inference workflows, memory and throughput optimisation, numerical debugging. Output-based pay, 100 openings, global remote, roughly 15 hours a week at $100–150/hour.

Refine CRM data models, arbitrate conflicting operational policies and document why you ruled the way you did, and design revenue workflows that hold up under vertical regulation. Four years with your hands actually in the system is the bar; the ad states outright that management-only exposure does not count. Remote contractor work.

Build and document the production pipelines you'd work on during a normal week, alongside experts from two other disciplines, so the outputs can be turned into the tasks and rubrics that train frontier models. $140–200/hour for 40 hours a week from 14 September to 10 October 2026. You must be based in the UK with the right to work there.