Staff Software Engineer, Physical AI for Robotics

Renesas Electronics Corp.; Farmington Hills (MI); Hybrid; USD 140,000 - 210,000; Full time

Job summary

Renesas Electronics Corp. seeks a Staff Engineer, Software – Physical AI to lead development and adoption of R-Car based platforms for next-generation robotic and Physical AI applications.

You will collaborate with customers, ecosystem partners, and internal teams to optimize AI workloads, deliver reference designs, and shape future R-Car software. The ideal candidate brings deep expertise in embedded Linux, heterogeneous compute, robotics software, and AI acceleration, with hands-on CPU/GPU/NPU

Qualifications

• BS/MS/PhD in Computer Engineering, Electrical Engineering, CS, Robotics or related field.
• 5+ years in embedded systems, robotics, AI, or high-performance compute platforms.
• Strong C/C++ with embedded Linux and hardware-software integration experience.

Responsibilities

• Lead technical efforts for Physical AI, humanoid robotics, and robotic compute platforms based on Renesas R-Car SoCs.
• Develop reference designs, proofs of concept, demos, and reusable customer solutions with partners.
• Support customer programs from architecture through bring-up, integration, debugging, and production.
• Analyze and optimize AI/robotics workloads: perception, SLAM, planning, control, inference.
• Lead system-level debugging across Linux, ROS2, GPUs/NPUs, drivers, and multicore systems.
• Balance workload partitioning across CPU/GPU/NPU/DSP for latency and power.

Skills

C/C++ development

Embedded Linux

ROS2

AI acceleration

Performance profiling

Systems debugging

Hardware-software integration

Education

BS/MS/PhD in Computer/Electrical Engineering, CS, Robotics or related

Tools

Renesas R-Car

Vulkan/OpenCL/OpenVX

Job description

Renesas Electronics Corp. seeks a Staff Engineer, Software – Physical AI to lead development and adoption of R-Car based platforms for next-generation robotic and Physical AI applications.

You will collaborate with customers, ecosystem partners, and internal teams to optimize AI workloads, deliver reference designs, and shape future R-Car software. The ideal candidate brings deep expertise in embedded Linux, heterogeneous compute, robotics software, and AI acceleration, with hands-on CPU/GPU/NPU