Principal Engineer Physical AI Systems Modeling
Core
Define and lead research in foundation model training, vision-language-action models, reinforcement learning, and generative models for humanoid and industrial robotics, translating research into hardware implementations.
Role type
Principal Engineer, Physical AI Systems Modeling
Builds
Virtual system world models, data curation pipelines, and hardware implementations for robotics
Domain
Robotics, Physical AI, Semiconductor
Deliverable
production ML models
Required skills
foundation model training and fine-tuning, vision-language-action models, reinforcement learning, generative modeling, robotics algorithms, system modeling, kinematics, dynamics, perception, planning, control, grasping, manipulation, trajectory generation, contact-rich interaction, data curation pipelines, sim-to-real workflows, algorithm-hardware co-design, digital ASIC design and verification, Python, C/C++
Preferred skills
Neuromorphic and in-memory computing, foundation model development for hardware generation (schematics, RTL)
Technologies
NVIDIA Isaac Sim, MuJoCo
Responsibilities
Define long-term Physical AI research direction and system architecture; Architect and maintain virtual system world models; Own technical architecture of data curation pipelines; Lead imitation-learning, reinforcement-learning, and sim-to-real workflows; Translate research into hardware implementations; Define and evaluate system-level performance trade-offs; Mentor engineers and researchers
Seniority
Principal, technical thought leader and strategy
