Turing review · AI Training & Data Labeling
Scientific Coding Trainer — Biology & Python (Turing)
What the work involves
Turing is building one of the most rigorous STEM AI training datasets in the industry, in partnership with NVIDIA. As a SciCode Trainer on the biology track, you'll author, implement, and review complex scientific coding problems used to train and evaluate frontier AI models.
What the tasks look like
Each task is a main problem plus at least three sub-problems that build progressively toward the solution. You write the problem specification, implement the golden solution in Python with complete unit test coverage, and design test cases that clearly discriminate correct from incorrect model outputs.
Tasks run through Turing's Central Task Platform with Tier 1 structure checks and Tier 2 quality rubrics, and are judged against Pass@K criteria across multiple LLM judges (GPT, Gemini, Nemotron). The goal is consistent L1 approval on first submission with a low rework rate.
Logistics
This is an 8-week contractor engagement at 40 hours per week with a 4-hour daily overlap with Pacific Time. The posting does not state an hourly rate — confirm pay during evaluation. Eligible locations: Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Pakistan, Indonesia, Kenya, Nigeria, Turkey, Vietnam.
What you'll do
- Write scientific problem specifications with a main problem and at least 3 progressive sub-problems
- Implement verified golden solutions in Python with complete unit test coverage
- Design test cases that differentiate correct from incorrect model outputs
- Run QC validation on Turing's Central Task Platform (Tier 1 and Tier 2 checks)
- Iterate on tasks based on QC feedback until they pass multi-model evaluation
- Join sync calls for reviews and standups during PST overlap hours
Requirements & eligibility
- Master's or PhD in Biology or a closely related field
- Strong Python programming skills with experience in scientific computing (NumPy, SciPy or domain-specific tools)
- Ability to write rigorous, well-posed scientific problems with clear constraints and expected outputs
- Prior experience in AI data annotation, research, or scientific writing is preferred
- Familiarity with LLM evaluation frameworks or coding benchmarks is an advantage
How to apply
Applications go directly to Turing. Read their terms before you sign up — and if anything feels off, run the scam check below first.
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