Physics - AI Training Expert (United Kingdom)
Posted Today by Anyone AI
Negotiable
Undetermined
Remote
London, England, United Kingdom
Summary: The role of Physics - AI Training Expert involves designing advanced physics problems for AI training and evaluation, ensuring each problem has a single verifiable correct answer. The expert will create rigorous, deterministic problems that challenge state-of-the-art AI systems and provide complete, verified solutions. The position requires strong expertise in physics and proficiency in Python, with a focus on technical precision and clarity in documentation.
Key Responsibilities:
- Design advanced physics problems for frontier AI training and evaluation
- Create deterministic problems with exactly one correct answer
- Write complete, verified solutions and clearly document the reasoning process
- Develop problems that test deep physical reasoning and multi-step analysis, not just memorization
- Use Python or specialized tools to build simulations, models, or computational workflows where relevant
- Ensure all outputs are technically precise, reproducible, and well-written in English
Key Skills:
- Bachelor's, Master’s, or PhD in Physics or a closely related field
- Strong research or industry experience involving theoretical, experimental, or computational physics
- Strong Python skills; comfort with scientific libraries such as numpy, scipy, or similar
- Solid understanding of modeling, simulation, numerical methods, and multi-step problem solving
- Ability to design original, difficult problems that reflect real physics workflows
- Excellent attention to detail and technical writing skills in English
- Experience with simulation tools or domain-specific physics software (e.g., finite element tools, circuit simulators, symbolic systems) is a plus
- Background in areas such as computational physics, statistical mechanics, electromagnetism, quantum mechanics, or related fields is a plus
- Experience evaluating model reasoning, benchmarking, or designing technical assessments is a plus
Salary (Rate): £32.00 hourly
City: London
Country: United Kingdom
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Location: Remote
Type: Contract / Part-time
Commitment: 20 to 40 hours per week
Compensation: Up to 40 USD / hr
Project duration: 2 months, with potential extension
Availability: Immediate start
About The Role
We create high-quality STEM training data for frontier AI models. Our data is used directly in training and evaluation pipelines at leading AI labs to improve model reasoning in technical domains. We are looking for experts in Physics to design rigorous, deterministic problems that are genuinely challenging for state-of-the-art AI systems. Each problem must have exactly one verifiable correct answer and be submitted together with a complete, verified solution.
What You’ll Do
- Design advanced physics problems for frontier AI training and evaluation
- Create deterministic problems with exactly one correct answer
- Write complete, verified solutions and clearly document the reasoning process
- Develop problems that test deep physical reasoning and multi-step analysis, not just memorization
- Where relevant, use Python or specialized tools to build simulations, models, or computational workflows
- Ensure all outputs are technically precise, reproducible, and well-written in English
What We’re Looking For
- Bachelor's, Master’s, or PhD in Physics or a closely related field
- Strong research or industry experience involving theoretical, experimental, or computational physics
- Strong Python skills; comfort with scientific libraries such as numpy, scipy, or similar
- Solid understanding of modeling, simulation, numerical methods, and multi-step problem solving
- Ability to design original, difficult problems that reflect real physics workflows
- Excellent attention to detail and technical writing skills in English
- Nice to have
- Experience with simulation tools or domain-specific physics software (e.g., finite element tools, circuit simulators, symbolic systems)
- Background in areas such as computational physics, statistical mechanics, electromagnetism, quantum mechanics, or related fields
- Experience evaluating model reasoning, benchmarking, or designing technical assessments