Assembling a world-class research group focused on making a vision a reality, unlocking new capabilities in autonomous agents.
Requirements
- Proficiency in frameworks like PyTorch or JAX, and hands-on experience training large models on distributed infrastructure.
- A willingness to dig into all levels of the stack—from modeling to debugging data pipelines or UX prototypes.
Responsibilities
- Invent and prototype new approaches in planning, memory, multi-agent systems, and learning from human feedback.
- Deploy at scale, with real users and datasets, running experiments across large compute clusters and iterating rapidly.
- Design practical systems, working closely with engineering and product teams to integrate research into production-ready tools.
- Define best practices around model evaluation, safety, and alignment, helping establish a research culture focused on impact and rigor.
- Mentor and collaborate, working with engineers, interns, and collaborators from different backgrounds to maximize team output.
Other
- A graduate degree (or equivalent experience) in machine learning, reinforcement learning, NLP, or related fields.
- A track record of high-quality research—through papers, open-source work, or real-world deployments.
- Passion for fast-paced, collaborative work and an eagerness to ship working systems—not just write about them.
- Availability for in-person work in the San Francisco Bay Area.
