Scientific Coding Expert - Biology and Python

Turing is collaborating with NVIDIA to develop one of the most rigorous STEM AI training datasets in the industry through the SciCode project. This initiative focuses on creating high-quality scientific coding tasks that 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. Your work will directly impact the development and assessment of frontier AI technologies.

Key Responsibilities:
- Write detailed scientific problem specifications that include one main problem and at least three logically connected sub-problems, each progressively building toward solving the main problem.
- Implement verified golden solutions in Python, ensuring complete unit test coverage for accuracy and reliability.
- Design discriminative test cases that effectively distinguish between correct and incorrect model outputs.
- 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 minimal rework, aiming for consistent first-time approval at Level 1 (L1).
- Participate in regular sync calls for reviews, feedback sessions, and project standups during overlapping hours with the team.

Required Qualifications:
- Master’s or PhD degree in Biology.
- Strong Python programming skills with experience in scientific computing.
- Ability to craft rigorous, well-posed scientific problems with clear constraints and defined expected outputs.
- Exceptional attention to detail to ensure tasks meet strict rubrics related to well-posedness, test case discriminativeness, scientific accuracy, and determinism.
- Prior experience in AI data annotation, research, or scientific writing.
- Familiarity with LLM evaluation frameworks or coding benchmarks.
- Experience with scientific computing libraries such as NumPy, SciPy, SymPy, or other domain-specific scientific tools.
- Published research or academic project experience in a STEM field is highly desirable.

Offer Details:
- Commitment required includes a 4-hour overlap with Pacific Standard Time (PST) and a 40-hour workweek.
- Engagement is on a contractor or freelancer basis, with no medical benefits or paid leave provided.
- The contract duration is 8 weeks.

This role offers a unique opportunity to contribute to pioneering AI research by developing scientifically rigorous coding tasks that push the boundaries of machine learning capabilities. If you have a strong STEM background, excellent Python skills, and a passion for scientific problem-solving, this position allows you to work at the intersection of AI and scientific innovation.