Energy Systems Problem Designer for AI Training

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 Energy Engineering and Energy Systems 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 energy engineering and energy systems 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 involving renewable energy, power generation, storage, grid systems, energy efficiency, thermodynamics, or energy economics
• Create scenarios requiring quantitative analysis of complex energy systems
• Where relevant, use Python, MATLAB, optimization software, or energy modeling tools to validate solutions
• Ensure all outputs are technically precise, reproducible, and well-written in English

What we’re looking for

• Master’s or PhD in Energy Engineering, Electrical Engineering, Mechanical Engineering, Energy Systems, or a closely related field
• Strong research or industry experience involving energy systems, renewable technologies, power systems, energy modeling, or energy optimization
• Strong quantitative, mathematical, and computational skills
• Solid understanding of energy conversion, system efficiency, optimization, and technical modeling
• Ability to design original, difficult problems that mirror real energy engineering workflows
• Excellent attention to detail and technical writing skills in English

Nice to have

• Experience with Python, MATLAB, HOMER, EnergyPlus, PyPSA, PLEXOS, OpenDSS, or similar energy modeling tools
• Background in renewable energy integration, batteries, grid optimization, power markets, or decarbonization
• Experience designing technical assessments, benchmarks, or computational energy models