Scientific Coding Expert - Chemistry and Python

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 designed to 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, particularly chemistry. Your work will directly impact the performance and accuracy of frontier AI systems.

Key Responsibilities:
- Write detailed scientific problem specifications that include one main problem and at least three logically connected sub-problems, progressively building toward the solution of the main problem.
- Implement verified golden solutions in Python, ensuring complete unit test coverage for all problems.
- Design discriminative test cases that effectively distinguish between correct and incorrect model outputs.
- Conduct quality control 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, targeting consistent first-submission approval at Level 1 (L1).
- Participate in regular sync calls for reviews, feedback sessions, and project standups during overlapping hours with the PST time zone.

Required Qualifications:
- Master’s or PhD degree in Chemistry.
- 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 correctness, and determinism.
- Prior experience in AI data annotation, scientific research, or scientific writing.
- Familiarity with large language model evaluation frameworks or coding benchmarks.
- Experience using scientific computing libraries such as NumPy, SciPy, SymPy, or other domain-specific scientific tools.
- Demonstrated research or academic project experience in a STEM domain, preferably with published work.

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. This is a contract assignment without 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 scientific AI models. If you have a strong background in chemistry and scientific programming, along with a passion for precision and quality in AI training data, this position is an excellent fit.