Scientific Coding Trainer (STEM/Python) · Turing Turing · TBD · Remote (select) · 3w ago TBD Remote (select) 3w ago

Benture; Brasil; Teletrabalho; BRL 288 000 - 575 000; Tempo integral

Resumo da oferta

Turing and NVIDIA collaborate on a rigorous STEM AI training dataset project. As a SciCode Trainer, you will author, implement, and review complex scientific coding problems that train frontier AI models.

This 8-week contractor engagement requires 40 hours per week with a 4-hour PST overlap. Responsibilities include writing problem specs, implementing Python solutions with tests, and designing discriminative test cases while ensuring high rubric compliance.

Qualificações

• Master's or PhD in a STEM discipline.
• Strong Python programming skills with hands-on experience in scientific computing.
• Ability to write rigorous, well-posed scientific problems with clear constraints and expected outputs.
• High attention to detail - tasks must meet strict rubrics for well-posedness, test case discriminativeness, scientific correctness, and determinism.
• Prior experience in AI data annotation, academic research, or scientific writing.
• Familiarity with LLM evaluation frameworks or coding benchmarks.
• Proficiency with scientific libraries such as NumPy, SciPy, SymPy, or domain-specific tools.
• Published research or academic project experience in a STEM domain is a strong plus.

Responsabilidades

• Write scientific problem specifications consisting of one main problem and a minimum of 3 logically connected sub-problems that progressively build toward the main 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.

Conhecimentos

Python programming

Scientific computing

Attention to detail

Problem writing

AI data annotation

LLM evaluation

Coding benchmarks

Formação académica

Master's or PhD in STEM

Ferramentas

NumPy

SciPy

SymPy

Descrição da oferta de emprego

Scientific Coding Trainer (STEM & Python) | Contractor | Remote (Select Countries)

Join Turing and NVIDIA in building one of the most rigorous STEM AI training datasets in the industry. As a SciCode Trainer, you’ll author, implement, and review complex scientific coding problems that directly train and evaluate frontier AI models. This is an 8-week contractor engagement requiring 40 hours per week with a 4-hour PST overlap.

Key Responsibilities

• Write scientific problem specifications consisting of one main problem and a minimum of 3 logically connected sub-problems that progressively build toward the main 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 a STEM discipline.
• Strong Python programming skills with hands-on experience in scientific computing.
• Ability to write rigorous, well-posed scientific problems with clear constraints and expected outputs.
• High attention to detail - tasks must meet strict rubrics for well-posedness, test case discriminativeness, scientific correctness, and determinism.
• Prior experience in AI data annotation, academic research, or scientific writing.
• Familiarity with LLM evaluation frameworks or coding benchmarks.
• Proficiency with scientific libraries such as NumPy, SciPy, SymPy, or domain-specific tools.
• Published research or academic project experience in a STEM domain is a strong plus.

Engagement Details

• Commitment: 40 hours/week with 4-hour PST overlap
• Type: Contractor/Freelancer (no medical or paid leave benefits)
• Duration: 8 weeks
• Eligible Locations: Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Indonesia, Kenya, Nigeria, Pakistan, Turkey, Vietnam