About the RoleYou'll drive original research at the boundaries of AI, working on new models, algorithms, and architectures for reasoning in complex environments. Your work will shape the scientific agenda of the lab and inform everything we build. You'll have autonomy to pursue fundamental research and see your ideas deployed in real-world settings.
Responsibilities- Formulate and explore open questions in deep learning, reinforcement learning, and agent-based AI.
- Develop novel architectures, algorithms, and theoretical insights.
- Collaborate with engineers to implement, experiment, and iterate rapidly.
- Publish, present, and contribute to the broader research community.
- Mentor and support the next generation of technical talent.
Requirements- Demonstrated track record of impactful AI/ML research (e.g., papers, open-source, or novel deployments).
- Deep expertise in at least one of: LLMs, RL, agent-based systems, generative modeling, theory of intelligence.
- Strong mathematical background (probability, optimization, statistics).
- Proficiency in Python and modern ML frameworks (e.g., PyTorch, JAX).
- Ability to turn theory into robust, practical code.
- Up-to-date on the latest research in LLMs from reading papers, articles, or re-implementing breakthroughs.
- Expertise in leveraging the latest AI tools (Cursor, Claude Code, Codex, etc) to increase productivity & code output while maintaining high code quality, maintainability, and structure.
