Physics Expert - AI Trainer (Uruguay)

Job description

- **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 ## **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** - **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