Materials Science Coding Expert (Python)
Listing checked September 8, 2026 · pay as published by Turing
Overview
Turing’s SciCode project is assembling one of the most demanding STEM AI training datasets in the industry. As a SciCode Trainer, you will craft, code, and validate intricate scientific problems in materials science that push frontier AI models to their limits. This direct contribution supports AI research by challenging models with precise, discriminative tasks. You will verify solutions in Python against strict quality rubrics and iterate with feedback from multiple LLM judges.
What You'll Do7
- 1Draft a scientific problem spec with a central challenge plus at least three connected sub-problems that build logically toward the main solution.
- 2Implement and test gold-standard solutions in Python, ensuring complete unit test coverage.
- 3Design test cases that clearly separate correct from incorrect model outputs, making them highly discriminative.
- 4Run QC checks on the Turing Central Task Platform, including Tier 1 structure checks and Tier 2 quality reviews.
- 5Revise tasks based on QC feedback to satisfy Pass@K evaluation criteria across different LLM judges such as GPT, Gemini, and Nemotron.
- 6Keep rework rates low and aim for first-time approval on L1 quality checks.
- 7Join sync calls for project standups, feedback, and collaborative reviews during overlap hours.
Requirements7
- 1Master's or PhD in materials science or a closely related field.
- 2Strong Python skills for scientific computing, with hands-on experience in libraries like NumPy, SciPy, or SymPy.
- 3Ability to write precise, well-posed scientific problems with clear constraints and expected outputs.
- 4Familiarity with LLM evaluation or coding benchmarks is a plus.
- 5Prior work in AI data annotation, research, or scientific writing helps.
- 6Attention to detail is key: tasks must pass strict rubrics for scientific correctness, determinism, and test quality.
- 7Published research or academic projects in a STEM domain demonstrate your depth.
Who Should Apply
A materials science researcher or grad student who codes comfortably in Python and enjoys crafting puzzles that test AI logic fits well. The role suits someone who can translate complex scientific concepts into clear, solvable problems with exact outcomes. If you don’t have strong Python skills or an advanced degree in materials science, this is not the right fit. Candidates often get rejected when their test cases are too easy or ambiguous, or when their solutions fail under strict unit test coverage. Rework is common when problem specifications lack logical progression or clear constraints, so precision matters from day one.
Pay and demand for Machine Learning & AI roles
AggregatedTypical pay
$70/hour
This role
Pay not disclosed
Most Machine Learning & AI roles pay $50–$100 per hour.
Based on 605 similar roles that publish pay · 102 publish only a top rate; those count at the rate they gave
Rates shown per hour. Yearly and monthly pay converted; one-time fees and non-USD pay are not included.
- Live similar roles
- 690
- Listed in last 30 days
- 295
- Remote
- 97%
Hiring most right now: micro1 (358) · SME Careers (111) · Mercor (101)
Most requested skills · share of roles
- python14%
- llm evaluation8%
- ai training6%
- quality assurance6%
Figures from Machine Learning & AI roles live on NearSkill when this page loaded. A role can close before you apply, so check the listing itself.
Compare your resume against these rolesLocation
Compensation
Undisclosed by Turing
Comparable roles pay
605 roles$50 – $100/ hr
Not this role’s pay. Turing has not published a range.
Confirmed during Turing profile screening.
Required Skills
Application Tip
Highlight a specific example where you designed a scientific problem or coding challenge with rigorous test cases—quantify the outcome (e.g., accuracy improvement, benchmark score). Emphasize your materials science expertise and Python proficiency (NumPy, SciPy), and mention any previous experience with LLM evaluation to stand out.
See NearSkill jobs more often in your search
Application & verification flow
1Instant rubric match
Your resume is scanned against this role’s requirements to check qualification fit.
2Screened before the employer sees it
Only profiles that clear screening are passed on.
3Outcome by email
We notify you at the address on your resume once the screening is reviewed.
Similar open positions
Explore active roles that match your skills and interests.
Turing
VerifiedScientific Coding Expert for Physics and Python AI Training
Turing's SciCode project builds a rigorous STEM dataset designed to train and assess frontier AI models. As a SciCode Trainer, you'll write scientific coding challenges rooted in physics and use python to craft verified solutions and tests. Each task weaves one core problem with several connected sub-problems that grow in complexity. Your work directly shapes how AI handles complex reasoning in science and programming. It's a contract position requiring a 4-hour overlap with PST and a commitment of 40 hours weekly for 8 weeks.
Turing
VerifiedMathematical Coding Specialist (Remote)
Turing is assembling one of the toughest STEM training datasets in AI, and the SciCode project sits at the center. You will design original scientific coding challenges that push frontier models like GPT, Gemini, and Nemotron to their limits. Each task you build becomes part of the training ground for the next wave of AI reasoning. Your work here directly influences how these models handle complex mathematics and real-world scientific computation. With a Python-heavy stack and a strong focus on rigor, the role suits someone who enjoys turning intricate math into clear, testable code.
Turing
VerifiedBiology Python Scientific Coding Contractor (Remote)
Turing, in partnership with NVIDIA, is assembling a rigorous STEM AI training dataset through the SciCode project. This initiative focuses on creating high-quality scientific coding tasks that help train and evaluate frontier AI models. As a SciCode Trainer, you will craft, implement, and review intricate scientific problems in biology, directly contributing to AI research that pushes the boundaries of what models can solve. Expect to work within a structured environment that demands precision, scientific accuracy, and a deep understanding of both biology and Python.
Turing
VerifiedChemistry Python Coding Trainer (Remote SciCode)
Turing is assembling a team of scientific coding experts for its SciCode project, an effort to build a rigorous STEM dataset for training frontier AI models. As a SciCode Trainer, you will author and review chemistry problems in Python, creating tasks that test and improve model reasoning. The work involves a blend of scientific writing, coding, and quality control, all aimed at producing data that meets strict evaluation standards. This is a remote, 8-week contract role requiring a 4-hour overlap with PST hours and a commitment of 40 hours per week.
Micro1
VerifiedMaterials Science Expert
This contract role places you at the center of an AI training project focused on computational materials science. You will create, solve, and validate engineering problems involving material structures, properties, and simulations. The work is fully remote and flexible, with about 15 hours per week. You will use Python and tools like LAMMPS, ASE, or pymatgen to build reproducible solutions that are both computationally sound and physically meaningful.
Mercor
VerifiedMaterial Science PhD Coding Experts
We're partnering with leading AI labs to build a fresh benchmark for scientific computing. Your work will involve creating original research problems that today's most capable models still fail. You'll pull source material from published papers, Kaggle datasets, open-source repositories, or your own designs, then turn them into executable prompts with strict grading rubrics. The role demands real depth in materials science and molecular modeling, plus working proficiency in Python or R and comfort with Git and Docker. This is a contract gig paying $70/hour, remote and part-time at 20+ hours weekly.