🛠 Tech Stack

💼 About This Role

You'll develop methods for self-improving AI agents that continually learn from experience, working with a world-class team on the frontier of AI. Your research will advance the field through open publishing and real-world impact at companies like 11x and Bilt Rewards.

🎯 What You'll Do

• Develop prompt optimization and system prompt learning for continuous agent learning
• Create methods for agents to auto-generate and test hypotheses in environments
• Improve learning efficiency from long-running agentic tasks
• Design and run scalable experiments to measure self-improvement

📋 Requirements

• Expertise in machine learning, particularly LLMs and continual learning
• Familiarity with agent frameworks and prompt optimization
• Track record of impactful research (publications or open-source contributions)

✨ Nice to Have

• Experience with long-context models
• Background in reinforcement learning
• Published work in AI safety or alignment

🎁 Benefits & Perks

• 🚀 Work on cutting-edge AI research
• 🏢 In-person collaboration in downtown SF
• 📝 Open publishing of research and code
• 🤝 Flat organization with no bureaucracy

📨 Hiring Process

Initial screen (30 min), technical screen (1-1.5 hours), paid in-person work trial (2 days onsite in SF).

🚩 Heads Up

• Requires 5 days in-person (no hybrid) with no remote option
• Culture signals a non-9-5 work expectation and ambiguity tolerance