Principal Engineer Physical AI Systems Modeling
Renesas Electronics2 days ago
Ottawa, CanadaStaff+
Responsibilities
- Define long-term Physical AI research direction and system architecture for humanoid and industrial robotics.
- Lead foundation model training and fine-tuning, vision-language-action model development, reinforcement learning, and generative modeling.
- Architect and maintain virtual system world models covering robotic hardware, sensors, dynamics, contact interactions, and environments.
- Own Physical AI data curation pipelines spanning simulation, synthetic data, real-world collection, teleoperation, multimodal synchronization, schemas, quality checks, dataset versioning, and reproducible evaluation.
- Lead imitation learning, reinforcement learning, domain randomization, sim-to-real, and real-to-sim workflows.
- Translate research into hardware implementations through algorithm–hardware co-design and validation.
- Define system-level performance and resource trade-offs for deployment and technical priorities.
- Mentor engineers and researchers and advise on multidisciplinary technical strategy.
Requirements
- Ph.D. in Robotics, Engineering Science, Computer Science, Electrical Engineering, Computer Engineering, Mechanical Engineering, Applied Mathematics, Physics, or a closely related field.
- At least 8 years of related research and engineering experience.
- Strong expertise in foundation model training and fine-tuning, vision-language-action models, reinforcement learning, and generative and world models for Physical AI.
- Deep expertise in robotics algorithms and system modeling, including kinematics, dynamics, perception, planning, control, grasping, manipulation, trajectory generation, and contact-rich interaction.
- Hands-on experience with NVIDIA Isaac Sim, MuJoCo, and similar physics-based simulation and virtual system modeling platforms.
- Experience designing Physical AI data curation pipelines and sim-to-real and real-to-sim workflows.
- Experience translating research into hardware implementations, including algorithm–hardware co-design and system-level validation.
- Experience with digital ASIC design and verification and collaboration across research, system architecture, RTL design, and verification.
- Strong software development experience in Python and C/C++ using CPU- and GPU-based environments, version control, testing, and reproducible experimentation.
- Publications in reputable robotics conferences and journals.
- Demonstrated technical thought leadership, recognized expertise, and ability to advise on long-term strategy and resolve complex multidisciplinary problems independently.
- Knowledge of neuromorphic and in-memory computing and modeling is advantageous.
- Knowledge of foundation model development and fine-tuning for hardware generation such as schematics and RTL is advantageous.
Benefits
- Competitive benefits package is offered alongside salary.
- Regular permanent employment.
- Remote work is not available.
Categories
About Renesas Electronics
Renesas Electronics designs and sells microcontrollers, analog and power ICs, and connectivity solutions for automotive, industrial, infrastructure and IoT manufacturers. Its portfolio spans embedded processing, power management and ADAS-ready components, sold directly and through channels to OEMs and Tier-1 suppliers, with software and development tools to integrate them. Founded in 2010 and headquartered in Tokyo, it is a public company on the Tokyo Stock Exchange and has expanded through acquisitions including Intersil and Dialog Semiconductor.