Physical AI Engineer – Simulation & Synthetic Data
Core
Build high-fidelity physics-based simulation environments and train reinforcement learning agents to transfer behaviors to physical robots.
Role type
Senior IC AI Robotics Engineer (Simulation & Synthetic Data)
Builds
Learning-driven robotic systems that interact with physical machines
Domain
Robotics, Reinforcement Learning, Simulation
Deliverable
production ML models
Required skills
reinforcement learning, imitation learning, simulation environment development, foundation model integration, Python, sim-to-real transfer, robotics controls, training pipeline scaling
Preferred skills
model-free or model-based RL at scale, domain randomization, system ID, hybrid control, real-time systems, robotics middleware
Technologies
NVIDIA Omniverse, Isaac Sim, USD, GPT-class models, Claude/Opus models
Responsibilities
Build physics-based simulation environments in NVIDIA Omniverse/Isaac Sim; Design and run RL/imitation learning pipelines using synthetic data; Train and tune policies for control, planning, and decision-making; Integrate foundation models for reasoning and task decomposition; Drive simulation-to-real transfer for physical robotic systems; Collaborate with robotics and controls engineers to deploy end-to-end systems
Seniority
Senior, hands-on IC
