Research Scientist (Intern)

What you'll do

• Design and train reasoning systems using reinforcement learning, reward models, and fine-grained supervision.
• Explore search, planning, oversight, and evaluation methods for geological reasoning.
• Build training pipelines, run large-scale experiments, and take research ideas through to production.

What they ask for

• Hands-on experience training large models; LLM experience is preferred but not required.
• Demonstrated reinforcement learning experience.
• Ability to work across research and engineering, including writing papers and debugging distributed training jobs.
• For interns: currently pursuing a graduate degree in machine learning, AI, or a related field, or an undergraduate with significant research experience; coursework or research experience in reinforcement learning, NLP, or deep learning.

Nice to have

• Familiarity with reward modeling, RLHF/RLAIF pipelines, search and planning, or AI alignment techniques.
• Strong project portfolio or publications demonstrating independent research ability; publications are a plus, not required.

Tools

RLHF, RLAIF, Monte Carlo Tree Search, LLMs

AI focus

Research and engineering for AI reasoning about geological evidence, including reinforcement learning, process reward models and verifiers, search and planning, scalable oversight, and evaluation.