STEM Annotator

STEM annotation is where model training gets genuinely hard. The work is verifying whether a model's chain of reasoning is correct, not merely whether its final answer matches; writing worked solutions that expose each step; and identifying the exact point at which an argument goes wrong. A plausible-looking derivation with one bad step is more damaging to a training set than an obviously wrong answer, and spotting that is the job.

Projects span secondary through graduate level across pure mathematics, statistics, physics, chemistry, biology and several engineering disciplines. You will be matched to your actual field rather than asked to cover all of them.

Corpshore runs annotation, evaluation and data collection for AI teams across 18+ countries in 35+ languages. Work is assigned by qualification and availability, not by location and every task shows its rate before you reserve it.

What you would be doing

• Verify model reasoning step by step, not just the final answer
• Write reference solutions with each step made explicit
• Identify precisely where a flawed argument breaks
• Rate difficulty and flag questions that are ambiguous or wrong as posed

What we need from you

• A degree, or equivalent demonstrable depth, in a STEM subject
• Comfort reading and writing mathematical notation
• A reliable internet connection and a device you can work on comfortably
• Ability to follow a written rubric precisely, including its edge cases
• Willingness to have your work reviewed, and to act on that review

Helpful, not required

• Postgraduate study or research experience
• Teaching, tutoring or marking experience
• LaTeX familiarity
• Previous annotation, transcription, moderation or research experience
• Comfort with spreadsheets or annotation tooling
• A subject you know unusually well, whatever it is