Staff Engineer Physical AI Systems
- Employment type
- Full-time · On-site
- Posted
- November 10, 2026
- Province
- Ontario (ON)
Hiring confidence: Sparse posting · 7/100
This posting is missing most of the signals we look for, or shows patterns common to listings that are not actively being filled. Check with the employer before applying. How this is scored
Job Overview
This role is based in Ontario. Renesas Electronics is hiring for this full-time position through Jobily, where you can check how well your resume matches the posting before you apply.
Market context
About this role in Ontario
Average salary for Staff Engineer Physical AI Systems in Ontario
We do not have a salary benchmark for this title in Ontario yet. The posting does not state a salary either.
NOC code
This posting has not been matched to a NOC 2021 unit group yet. Use the NOC finder to identify the code from the duties listed above.
Typical qualifications for Canadian employers
- Experience developing and validating Physical AI systems
- Expertise in system engineering
- Knowledge of humanoid and industrial robotics
- Proficiency in virtual and hybrid system modeling
- Experience with algorithm-hardware co-design
Fit check
Is this role right for you?
Top skills this posting asks for:
- Physical AI systems
- System engineering
- Robotics
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What you'll do
- Develop technologies related to Physical AI systems models and dataflow
- Design and validate systems for humanoid and industrial robotics
- Perform hands-on design work
- Conduct virtual and hybrid system modeling
- Execute algorithm-hardware co-design
- Validate experimental systems
- Collaborate across disciplines to achieve project goals
- Contribute to the Pathfinding Studio within the Engineering Innovation Office
What you'll need
- Experience developing and validating Physical AI systems
- Expertise in system engineering
- Knowledge of humanoid and industrial robotics
- Proficiency in virtual and hybrid system modeling
- Experience with algorithm-hardware co-design
- Ability to perform experimental validation
- Cross-disciplinary collaboration skills