Researcher

About the Company

We're building autonomous research agents for recursive self-improvement (multi-agent systems that propose, run, and analyze machine learning experiments). We're a small team based in San Francisco.

Responsibilities

• Identify research questions that meaningfully change agent capabilities
• Design and run experiments end-to-end from problem framing to write-up
• Develop new methods spanning RL, LLMs, agentic systems, and multi-agent coordination
• Work closely with engineers to transition promising methods into production
• Read deeply across literature and bring useful work into the team
• Help shape the team's problem selection process

Requirements

• 5+ years of hands-on research experience in industry or academia
• Strong track record in RL, LLMs, agentic ML, or multi-agent systems
• Published research at NeurIPS, ICML, ICLR, COLM, RLC, or comparable venues
• Proficiency in PyTorch, Jax, or equivalent
• Experience designing and running experiments at scale
• Strong written communication skills for summarizing research findings
• Ability to navigate ambiguity and work with open-ended problems

Preferred Qualifications

• PhD in ML, statistics, computer science, or adjacent fields
• Open-source contributions to ML research infrastructure
• Experience with tool use, long-horizon planning, or multi-agent coordination