Research Scientist - Robot Learning & RL

I’m working with a frontier AI research lab building low-latency models that help AI understand, act and cooperate with people in real time.

Starting with games and simulation, they’re researching how agents learn, coordinate and adapt alongside humans-and how these capabilities could transfer into robotics.

Supporters include Supercell, General Catalyst and South Park Commons, alongside participation in NVIDIA’s Inception Program.

This is an opportunity to own original research and help shape an early direction spanning reinforcement learning, embodied AI and human-robot collaboration.

You’ll work on:

• Developing policies using imitation learning, offline RL and online RL
• Building simulation environments and evaluations for control, planning and cooperation
• Researching world models, hierarchical policies and adaptation across tasks
• Exploring transfer from games and simulation into robotics
• Connecting learned policies with perception, memory and conversational behavior

• PhD in robotics, ML, computer science or equivalent original research experience
• Strong publications at venues such as NeurIPS, ICLR, ICML, CoRL, RSS, ICRA or IROS
• Deep reinforcement learning knowledge and hands-on policy development
• Strong Python and PyTorch skills
• Experience with simulation, embodied learning, robotic control or interactive environments
• Enthusiasm for exploratory research and full-time onsite work in San Francisco
• Imitation learning, world models, sim-to-real or human-AI cooperation experience is especially valuable.