LLM Scientist AI for Science

You will research, train, and optimize LLM-based and agentic AI solutions for scientific problems. You will create scientific-data workflows, improve reinforcement-learning and agentic systems, collaborate with domain scientists, contribute training infrastructure and open-source tools, and set a research agenda for high-risk, high-reward AI-for-science work.

Responsibilities

• Train and optimize LLM-based solutions for scientific applications
• Design workflows for high-quality scientific data creation at scale
• Develop reinforcement-learning and agentic systems for natural-science challenges
• Collaborate with domain scientists to identify opportunities and refine models
• Improve infrastructure for scientific model training
• Contribute open-source AI tools for science
• Set a research agenda for AI in science

Requirements

• LLMs, deep learning, or agentic AI experience
• Experience applying AI to real-world problems
• Knowledge of LLM architectures and post-training
• PyTorch, TensorFlow, or JAX
• Model optimization and scaling
• Fine-tuning
• RLHF
• Knowledge of a natural-science domain
• Scientific computing
• Numerical methods
• HPC
• Software engineering
• Ability to communicate AI concepts to non-experts
• Data pipelines
• Model deployment

Benefits

• Healthcare coverage
• Parental leave
• Retirement plans
• Relocation support
• Wellness programs
• Meal allowances
• Transportation allowances