About the Role
You will build robotics environments, evaluations, agent systems, and post-training methods. You will train agents using reinforcement learning, world modeling, imitation learning, planning, and multimodal perception, using feedback from simulations and deployed robots while addressing safety and hardware constraints.
Requirements
•Experience in robotics, embodied AI, reinforcement learning, imitation learning, control, world models, simulation, computer vision, agent evaluation, or physical-world production systems
•Experience building and debugging model-training, post-training, agent, or evaluation loops
•Experimental judgment, including baselines, trace inspection, and failure attribution
•Python
•Ability to build reproducible artifacts for researchers and engineers
•Ability to own ambiguous problems and communicate with partners
Responsibilities
•Build simulation and real-world environments for training, evaluation, and sim-to-real comparison
•Develop long-horizon agents that perceive, plan, act, remember, and recover under hardware constraints
•Combine offline and online reinforcement learning, demonstrations, interventions, and outcome feedback
•Design rewards and evaluations for task success, safety, adaptation, and continual improvement
Benefits
•Flexible work
•Visa sponsorship and relocation support
•Team off-sites and conference attendance
