ML Research Scientist, Scientific Evaluations

Highlights

• Design science evals and RL environments for frontier LLMs.
• Build pipelines turning papers and protocols into training environments.
• Prototype reward designs and integrate envs into training loops.

What they offer

• Bonus potential and early-stage equity
• Medical, dental, and vision coverage
• Employer-paid life and disability insurance
• Flexible time off with company holidays
• Paid parental leave
• Educational assistance program
• Commuter benefits and subsidized lunch

Ideal candidate

Creative ML researcher passionate about science who thrives in ambiguity and loves turning real-world workflows into rigorous evaluations for frontier models.

Requirements

• Experience applying ML or computation to biology, chemistry, or material sciences
• Strong track record of creating environments or evaluations for model training
• Experience building large, complex data pipelines for model training or production
• Strong prototyping and coding skills, comfortable iterating quickly in Python
• Creativity and research intuition to design experiments and navigate ambiguity
• Solid software engineering fundamentals and shared infrastructure integration