Posted Sep 24, 2026 12 views
Turing is developing one of the most rigorous STEM AI training datasets in the industry through its SciCode project. This initiative focuses on creating high-quality scientific coding tasks that help train and evaluate advanced AI models. As a SciCode Trainer, you will play a vital role in cutting-edge AI research by authoring, implementing, and reviewing complex scientific problems across core STEM disciplines, primarily physics. Your work will directly influence the quality and effectiveness of AI training data.
Key Responsibilities:
- Write detailed scientific problem specifications that include one main problem and at least three logically connected sub-problems, each progressively building toward the solution of the main problem.
- Implement verified golden solutions in Python with comprehensive unit test coverage to ensure correctness and reliability.
- Design discriminative test cases that effectively distinguish between correct and incorrect outputs generated by AI models.
- Conduct quality control (QC) validation checks on the Turing Central Task Platform (CTP), including Tier 1 structural checks and Tier 2 quality rubrics.
- Iterate on tasks based on QC feedback to meet Pass@K evaluation criteria across multiple large language model (LLM) judges such as GPT, Gemini, and Nemotron.
- Maintain a high standard of output quality with a low rework rate, aiming for consistent first-time approval (L1) on submissions.
- Participate in regular sync calls for reviews, feedback sessions, and project standups during overlapping hours with the PST time zone.
Required Qualifications:
- Master’s degree or PhD in Physics.
- Strong Python programming skills with experience in scientific computing.
- Ability to write rigorous, well-posed scientific problems with clear constraints and expected outputs.
- Exceptional attention to detail to ensure tasks meet strict rubrics for well-posedness, test case discriminativeness, scientific accuracy, and determinism.
- Prior experience in AI data annotation, scientific research, or scientific writing.
- Familiarity with LLM evaluation frameworks or coding benchmarks.
- Experience using scientific computing libraries such as NumPy, SciPy, SymPy, or other domain-specific tools.
- Published research or academic project experience in a STEM field is highly desirable.
Preferred Qualifications and Offer Details:
- Commitment to a 40-hour workweek with a required 4-hour overlap with Pacific Standard Time (PST).
- Engagement as a contractor or freelancer for an 8-week duration, with no medical benefits or paid leave.
This role offers a unique opportunity to contribute to pioneering AI research by shaping the datasets that train next-generation models. Candidates who are detail-oriented, scientifically rigorous, and passionate about AI and STEM disciplines will find this position rewarding and impactful.
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