Remote Scientific Coding Expert - Material science and Python

Turing Global India; United States; Remote; USD 83,000 - 124,000; Full time

Job summary

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. The role requires writing problem specifications with sub-problems, implementing verified Python

Qualifications

• Master's or PhD in Materials Science or related field, with strong Python and scientific computing experience.
• Ability to write rigorous, well-posed scientific problems with clear constraints and expected outputs.
• Experience in AI data annotation or scientific writing; familiarity with LLM evaluation frameworks.
• Proficiency with NumPy, SciPy, and SymPy; domain-specific scientific tools knowledge.

Responsibilities

• Write scientific problem specifications consisting of one main problem and a minimum of 3 sub-problems, all logically connected.
• 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.

Skills

Python programming

AI data annotation

Attention to detail

LLM evaluation frameworks

NumPy

SciPy

SymPy

Education

Master's or PhD in Materials Science or related field

Tools

NumPy

SciPy

SymPy

Job description

Role Overview:

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.

Responsibilities:

• 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

Required Qualifications:

• 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

Offer Details:

• Commitments Required: Overlap of 4 hours with PST and 40 hrs/week
• Engagement type: Contractor assignment/freelancer (no medical/paid leave)
• Duration of contract: 8 weeks