Physics Scientific Coding Task Author

About OpenTrain

OpenTrain AI is the hiring and contracting organization for this role and the #1 platform for finding and building careers in AI training and data labeling. OpenTrain helps contributors discover specialized projects, build a professional profile, and apply in minutes as they grow experience in this fast-moving field.

Creating an OpenTrain account is free, giving you a place to develop a lasting portfolio of AI training work while contributing your physics and programming expertise to advanced model development.

About AI Training Work

AI training is the human side of building artificial intelligence. Experts create, review, and evaluate examples that help models produce more accurate, useful, and reliable results. In coding and scientific projects, this includes writing benchmark problems, developing reference solutions, and judging whether model outputs satisfy technical requirements.

This work is part of a rapidly growing technology field and is often flexible and remote, making it possible to contribute around other professional or academic commitments.

The Role

OpenTrain is seeking a Scientific Coding AI Training Expert to author and assess demanding physics and scientific-computing tasks for advanced AI model training and evaluation. You will combine physics subject-matter expertise with Python development, scientific writing, and careful quality judgment.

Each task must be logically structured, scientifically correct, deterministic, and capable of distinguishing strong model outputs from incorrect ones. This is an intermediate-level, part-time contractor opportunity requiring 20 or more hours per week.

• Subject area: Physics and scientific computing
• Work type: Contractor and part time
• Time requirement: 20+ hours per week
• Working language: English
• Eligible countries: Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Pakistan, Indonesia, Kenya, Nigeria, Türkiye, and Vietnam

What You'll Do

You will create complete, technically rigorous coding tasks and the materials needed to evaluate model-generated solutions. The work requires precision from initial problem design through testing, review, and revision.

• Write scientific problem specifications with one central problem and at least three connected sub-problems that build toward a final solution.
• Implement verified Python solutions with complete unit test coverage.
• Design test cases that distinguish correct outputs from incorrect model outputs.
• Check tasks for well-posedness, scientific correctness, determinism, and test-case discrimination.
• Refine tasks in response to quality feedback and maintain strong first-submission quality.
• Participate in review sessions, feedback discussions, and project standups during the required overlap period.

Required Qualifications

This role requires advanced physics training and strong scientific-computing ability. You should be comfortable translating complex scientific concepts into precise, testable programming tasks with clear constraints and expected outputs.

• Master's degree or PhD in Physics
• Strong Python programming and scientific-computing skills
• Ability to write rigorous, well-posed scientific problems
• Ability to define clear constraints and expected outputs
• Sound judgment when assessing scientific correctness, determinism, and discriminative test cases
• Intermediate experience level

Helpful Background

The following experience can strengthen your ability to design and evaluate high-quality scientific coding benchmarks. These areas are valuable because they connect subject expertise with reliable model assessment and reproducible solution development.

• AI data annotation experience
• Experience with LLM evaluation frameworks or coding benchmarks
• Scientific research or scientific writing experience
• Familiarity with NumPy, SciPy, SymPy, or other scientific tools
• Published research or academic project experience in a STEM field

Build Your AI Training Career

AI training contributors help shape how modern AI systems solve problems, follow instructions, and handle specialized knowledge. By bringing physics expertise to coding evaluation, you can work directly on the quality standards used to assess advanced models.

OpenTrain provides one place to manage your AI training opportunities, showcase credible experience, and build a portfolio that supports longer-term growth in data labeling and AI development.

• Create a free OpenTrain account.
• Build a profile around your physics and scientific-computing experience.
• Apply for this opportunity in minutes.
• Use completed work to strengthen your AI training portfolio.