Staff Engineer Physical AI Systems

Posted Yesterday
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Ottawa, ON, CAN
Hybrid
Senior level
3D Printing
The Role
Develop and validate Physical AI systems for humanoid and industrial robotics. Responsibilities include robotics hardware and mechanical subsystem design, electromechanical integration, simulation, learning-based perception and control, virtual system modeling, neuromorphic computing evaluation, data and sim-to-real workflows, and system-level analysis of power, latency, compute, thermal, and performance trade-offs.
Summary Generated by Built In
Job Description

We are seeking a Staff Engineer (Physical AI - System Engineering) to join the Pathfinding Studio within the Engineering Innovation Office. In this role, you will develop and validate technologies related to Physical AI systems models and dataflow for humanoid and industrial robotics. The role combines hands-on design, virtual and hybrid system modeling, algorithm–hardware co-design, experimental validation, and cross-disciplinary collaboration to achieve project milestones.

Responsibilities:

· Contribute to Physical AI related technology development for humanoid and industrial robotics, translating requirements into hardware, mechanical, compute, and software design choices.

· Design, prototype, integrate, and validate humanoid hardware and mechanical subsystems, including articulated hands and arms, actuator and sensor integration, and electromechanical interfaces.

· Develop and evaluate learning-based perception, planning, control, and manipulation workflows, including foundation models, vision-language-action models, imitation learning, and reinforcement learning as appropriate to project objectives.

· Develop and maintain virtual system models and robotics hardware and software infrastructure for the lab environment.

· Evaluate and prototype neuromorphic and similar ultra-low-power computing approaches for humanoid sensing, perception, and control; integrate candidate computing platforms into system demonstrations.

· Develop and apply best practices for reproducible simulation, data collection, training, and evaluation; investigate complex failure modes through in-depth analysis of variable factors and validate sim-to-real transfer against system requirements.

Qualifications

· Six years of related research and engineering experience with a Master’s degree, or three years with a PhD, demonstrating specialized depth and/or breadth of expertise and recognition as a technical expert within a team or department.

· Strong foundation in mathematics, physics, and robotics, including kinematics, dynamics, perception, planning, control, grasping, manipulation, and contact-rich interaction.

· Hands-on experience with NVIDIA Isaac Sim, MuJoCo, or comparable physics-based simulation and virtual system modeling platforms, including validation against physical hardware.

· Hands-on experience with mechanical CAD and electronic subsystem and PCB design and tools targeting robotics.

· Experience with learning-based robotics methods, such as foundation model adaptation, vision-language-action models, imitation learning, reinforcement learning, or generative and world models.

· Experience with simulation and real-world data collection, data quality, reproducible evaluation, and sim-to-real workflows; strong Python and C/C++ development skills in embedded, and distributed CPU-, or GPU-based environments.

· Experience with electromechanical integration, actuator and sensor selection and sensor modeling, and evaluation of mechanical constraints for articulated hands, arms, or other humanoid mechanisms.

· Knowledge in Neuromorphic and in-memory computing and modeling considered an advantage.

· Ability to measure and analyze system-level trade-offs in power and energy consumption, latency, compute resources, thermal behavior, and task performance.

· Experience translating algorithms into hardware implementations and collaborating with electronics, system architecture, RTL design, and verification teams; digital ASIC design and verification experience is an asset.

Education:

Master’s degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Engineering, Computer Science or a closely related field is the minimum educational requirement.

PhD in a relevant field is preferred.

Additional Information

Renesas is an embedded semiconductor solution provider driven by its Purpose, To Make Our Lives Easier. With a global team of over 21,000 engineers and problem solvers in more than 30 countries, we offer the opportunity to work on world‑leading technology for Automotive, Industrial, Infrastructure, and IoT, shaping a safer, healthier, greener, and smarter future.

At Renesas, TAGIE is our culture, grounded in being Transparent, Agile, Global, Innovative, and Entrepreneurial. It shapes how we work, grow and deliver on our purpose together. This collaborative spirit and mindset drive our semiconductor technology to transform industries and impact millions of lives.

We believe in rewarding our employees with a competitive benefits package alongside their salary. More information will be provided during the hiring process.

Are you ready to join our team and shape the future with us?

Export Control Compliance Condition

Renesas Canada must at all times comply with U.S. and Canadian export control legislative requirements. Current U.S. export control laws require that Renesas Canada obtain a U.S. government export license prior to employing persons in positions with access to certain technology. All positions at Renesas Canada have direct or indirect access to this technology.   As a result, it is necessary for Renesas Canada to determine if it would need an export license for new employees. To do so, we ask all candidates for employment whether their most recent country of citizenship or permanent residence is one of the countries specified in the export controls laws or regulations.

Renesas recognizes that you are entitled to human rights and privacy protections in the workplace and takes these obligations seriously. As such, we want you to know that your decision to complete the export control questions is entirely voluntary. Regrettably, should you choose not to complete these questions, we cannot consider you for employment because doing so would jeopardize our ability to comply with the applicable export controls laws. Should you choose to complete the questions, we will use the information collected only to determine if we would need an export license to employ you and not for any other purpose. 

Successful candidates must be eligible to meet the requirements of U.S. export control regulations, including (if applicable) the issuance of any required export license prior to starting employment at Renesas Canada. The decision whether to or not to file or pursue an export license application is at the sole discretion of Renesas Canada.

Skills Required

  • Master's degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Engineering, Computer Science, or a closely related field
  • Six years of related research and engineering experience with a Master's degree, or three years with a PhD
  • Strong foundation in mathematics, physics, and robotics, including kinematics, dynamics, perception, planning, control, grasping, manipulation, and contact-rich interaction
  • Hands-on experience with NVIDIA Isaac Sim, MuJoCo, or comparable physics-based simulation and virtual system modeling platforms
  • Experience validating simulations and virtual system models against physical hardware
  • Hands-on experience with mechanical CAD and electronic subsystem and PCB design tools for robotics
  • Experience with learning-based robotics methods, including foundation model adaptation, vision-language-action models, imitation learning, reinforcement learning, generative models, or world models
  • Strong Python and C/C++ development skills in embedded and distributed CPU- or GPU-based environments
  • Experience with simulation and real-world data collection, data quality, reproducible evaluation, and sim-to-real workflows
  • Experience with electromechanical integration, actuator and sensor selection, sensor modeling, and mechanical constraint evaluation
  • Ability to analyze power and energy consumption, latency, compute resources, thermal behavior, and task-performance trade-offs
  • Experience translating algorithms into hardware implementations and collaborating with electronics, system architecture, RTL design, and verification teams
  • PhD in a relevant field
  • Knowledge of neuromorphic and in-memory computing
  • Digital ASIC design and verification experience

Renesas Electronics Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Renesas Electronics and has not been reviewed or approved by Renesas Electronics.

  • Fair & Transparent Compensation — Feedback suggests pay is generally fair-to-good across many roles, with base pay aligned to prevailing market levels in multiple U.S. locations. Engineering and leadership tracks can be competitive on total compensation, reinforcing a sense that pay can meet market expectations in key job families.
  • Healthcare Strength — Feedback suggests core medical, dental, and vision coverage is solid and well-regarded by employees. Day-one eligibility in U.S. roles is described, supporting confidence in access and continuity of care.
  • Leave & Time Off Breadth — Feedback suggests PTO, paid holidays, sick time, and parental leave provide a comprehensive time-off framework. Company initiatives like Renesas Day and meeting-light Focus Fridays further support time away and balance.

Renesas Electronics Insights

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The Company
HQ: Tokyo
10,040 Employees

What We Do

We're the world's leading semiconductor manufacturer. Our mission is to make our lives easier and a world that's safer, healthier, greener, and smarter.

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