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Scientific Coding - Material science and Python

per hour

Contractor Remote Last verified 21 Jul 2026

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About the Role

Turing is building one of the most rigorous STEM AI training datasets in the industry. The SciCode project involves creating high-quality scientific coding tasks that are used to train and evaluate frontier AI models. As a SciCode Trainer, you will be directly contributing to cutting-edge AI research by authoring, implementing, and reviewing complex scientific problems across core STEM disciplines.

What You'll Do

Write scientific problem specifications consisting of one main problem and a minimum of 3 sub-problems, all logically connected and progressively building toward the main problem solution Implement verified golden solutions in Python with complete unit test coverage
Design discriminative test cases that clearly differentiate correct from incorrect model outputs Run QC validation checks on the Turing Central Task Platform (CTP) including Tier 1 structure checks and Tier 2 quality rubrics Iterate on tasks based on QC feedback to meet Pass@K evaluation criteria across multiple LLM judges (GPT, Gemini, Nemotron)
Maintain high output quality with a low rework rate, targeting consistent L1 approval on first submission
Participate in sync calls for reviews, feedback sessions, and project standups during overlap hours

You're a Good Fit If You

Required skills: Materials and Applied Chemistry
Master's or PhD in Material science or related field.
Strong Python programming skills with experience in scientific computing
Ability to write rigorous, well-posed scientific problems with clear constraints and expected outputs
Attention to detail - tasks must meet strict rubrics for well-posedness, test case discriminativeness, scientific correctness, and determinism
Prior experience in AI data annotation, research, or scientific writing
Familiarity with LLM evaluation frameworks or coding benchmarks
Experience with libraries such as NumPy, SciPy, SymPy, or domain-specific scientific tools .
Published research or academic project experience in a STEM domain Quality Standards

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Role Highlights

Pay

Pay varies

Contract

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Location

Remote

Pay & Payout

Independent contractor engagement through Turing. Apply via the link below - Turing handles vetting, onboarding and payment.

Common Questions

Turing has a reliability rating of very reliable based on the listings we track, with an onboarding time of 5-14 days. See our full Turing review for the details behind that rating.

Applying takes you to Turing's own website, where the application is completed. We are not a recruiter or employer and do not process applications directly - we may be recorded as the referring source.

Pay varies - Independent contractor engagement through Turing. Apply via the link below - Turing handles vetting, onboarding and payment.

Write scientific problem specifications consisting of one main problem and a minimum of 3 sub-problems, all logically connected and progressively building toward the main problem solution Implement verified golden solutions in Python with complete unit test coverage Design discriminative test cases that clearly differentiate correct from incorrect model outputs Run QC validation checks on the Turing Central Task Platform (CTP) including Tier 1 structure checks and Tier 2 quality rubrics Iterate on tasks based on QC feedback to meet Pass@K evaluation criteria across multiple LLM judges (GPT, Gemini, Nemotron) Maintain high output quality with a low rework rate, targeting consistent L1 approval on first submission

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