Materials Science Python Task Author

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. OpenTrain AI is recruiting contractors for specialized projects where expert contributors help shape how advanced AI systems learn, reason, and perform.

Creating an OpenTrain account is free, and contributors can build a profile that showcases credible AI training experience and supports long-term growth in this rapidly expanding field.

• Remote opportunities for contributors with specialized technical expertise
• A profile designed to help you build a durable AI training portfolio
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About AI Training and Coding Evaluation

AI training is the human side of building artificial intelligence. People create examples, review model outputs, and develop evaluation data that helps modern systems become more accurate, reliable, and useful.

In this role, you will combine materials science knowledge with Python programming to create challenging scientific tasks. Your work will help evaluate whether AI models can produce logically structured, scientifically correct, and reproducible solutions.

• Contribute directly to the development and evaluation of AI models
• Use scientific expertise in a cutting-edge AI training environment
• Work remotely with a structured, project-based assignment

The Role

OpenTrain is seeking an intermediate-level Materials Science Python Task Author to create rigorous scientific coding tasks for AI model training and evaluation. You will write well-posed problems, implement verified Python solutions, and design tests that meaningfully distinguish correct outputs from incorrect ones.

This is an 8-week remote contractor assignment for candidates located in Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Pakistan, Indonesia, Kenya, Nigeria, Turkey, or Vietnam. The assignment requires 40 hours per week, including four hours of overlap with Pacific Time. Compensation is not disclosed.

• Contractor assignment lasting 8 weeks
• 40 hours per week, including 4 hours of Pacific Time overlap
• Candidates must be located in one of the listed eligible countries
• English-language work

What You’ll Do

You will develop scientific coding problems that are useful for evaluating model performance and robust enough for consistent review. Each task should have a clear structure, scientifically sound assumptions, and expected outputs that can be tested deterministically.

• Write scientific problem specifications with one main problem
• Create at least three connected, progressively challenging sub-problems
• Implement verified Python solutions
• Provide complete unit test coverage
• Design discriminative test cases that separate correct and incorrect model outputs
• Review task quality against defined rubrics
• Revise tasks based on feedback
• Participate in review discussions and project coordination

Requirements and Helpful Background

A master’s degree or PhD-level knowledge in materials science or a related field is required. You should also bring strong Python programming and scientific-computing skills, along with the ability to write rigorous scientific problems with clear constraints and expected outputs.

This work requires careful judgment about scientific correctness, determinism, well-posedness, test-case discrimination, and the quality of model-generated outputs. Experience with AI data annotation, LLM evaluation frameworks, coding benchmarks, scientific research, or scientific writing is valuable.

• Master’s or PhD in materials science or a related field
• Strong Python programming and scientific-computing skills
• Ability to design logically connected scientific problems
• Experience implementing verified solutions and comprehensive unit tests
• Ability to create discriminative test cases
• Strong judgment regarding correctness, determinism, and well-posedness
• Familiarity with NumPy, SciPy, SymPy, or domain-specific scientific tools is helpful
• Published research or academic STEM project experience is relevant

Who Should Apply

This opportunity is suited to a materials science specialist who enjoys translating technical knowledge into precise, testable programming problems. It may be a strong fit if you have worked in scientific research, computational materials science, scientific writing, coding benchmark development, or LLM evaluation.

The structured role data lists a minimum commitment of 20+ hours per week, while this specific 8-week assignment requires 40 hours per week and Pacific Time overlap.

• Materials science researchers with strong programming ability
• Scientific programmers who can reason about domain correctness
• Technical writers who can express complex problems precisely
• Experts interested in contributing to AI model evaluation
• Candidates comfortable reviewing and improving work against formal rubrics

How to Apply Through OpenTrain

Create a free OpenTrain account, build a profile that reflects your materials science and Python experience, and apply for the assignment in minutes. Highlight relevant research, academic projects, scientific-computing work, publications, or experience with coding evaluation and AI training.

As you contribute, your OpenTrain profile can help document your experience and support a longer-term career in AI training and data labeling.

• Create or update your free OpenTrain profile
• Showcase materials science, Python, and scientific-computing expertise
• Include relevant research, publications, or evaluation experience
• Confirm your location and availability for the assignment
• Apply through OpenTrain