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Staff Engineer, Software – Physical AI

Job in Farmington Hills, Oakland County, Michigan, USA
Listing for: Renesas Electronics Corporation
Full Time position
Listed on 2026-10-08
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Robotics, Unix/Linux
Salary/Wage Range or Industry Benchmark: 140000 - 190000 USD Yearly USD 140000.00 190000.00 YEAR
Job Description & How to Apply Below
Job Description

Farmington Hills, MI - Hybrid

The HPC SoC Business Division is seeking a Staff Engineer, Software – Physical AI to drive customer and ecosystem adoption of Renesas R-Car SoCs for next-generation robotic and Physical AI platforms.

This role will provide technical leadership for humanoid robots, autonomous systems, embodied AI, and advanced robotic platforms by combining expertise in embedded systems, heterogeneous computing, AI acceleration, robotics software, and the mathematical foundations of Physical AI. The successful candidate will work directly with customers, ecosystem partners, and internal engineering teams to develop reference platforms, optimize AI workloads, and shape future R-Car products.

Key Responsibilities

  • Serve as technical lead for Physical AI, humanoid robotics, autonomous systems, and robotic compute platforms based on Renesas R-Car SoCs.
  • Collaborate with robotics and ecosystem partners to develop reference designs, proofs of concept, demonstrations, and reusable customer solutions.
  • Support customer programs from architecture definition through platform bring-up, software integration, debugging, optimization, validation, and production.
  • Analyze and optimize AI and robotics workloads including perception, sensor fusion, localization, mapping (SLAM), planning, navigation, manipulation, control, and AI inference.
  • Lead system-level debugging across Linux, ROS2, AI runtimes, GPU/NPU accelerators, device drivers, firmware, memory management, IPC, and heterogeneous multicore systems.
  • Optimize workload partitioning across CPU, GPU, NPU, DSP, and dedicated accelerators while balancing latency, throughput, memory bandwidth, and power consumption.
  • Support GPU compute technologies including Vulkan, Vulkan Compute, OpenCL, OpenGL ES, and OpenVX.
  • Develop performance models for AI and robotic systems by analyzing compute intensity, memory movement, data locality, accelerator utilization, and end-to-end latency.
  • Support customer RFIs, RFQs, architecture reviews, design reviews, technical workshops, and debug engagements.
  • Work with global engineering teams to define future requirements for R-Car SoCs, AI software, tools, and robotic reference platforms.
Qualifications

Required Qualifications

  • BS/MS/PhD in Computer Engineering, Electrical Engineering, Computer Science, Robotics, Applied Mathematics, or related field.
  • 5+ years of experience in embedded systems, semiconductor application engineering, robotics, AI, autonomous systems, or high-performance compute platforms.
  • Strong C/C++ software development and debugging experience.
  • Deep understanding of SoC architecture, memory subsystems, firmware, operating systems, device drivers, middleware, and hardware accelerators.
  • Extensive experience with Embedded Linux, Ubuntu, BSPs, bootloaders, Linux kernel, and system-level debugging.
  • Strong understanding of heterogeneous compute architectures, DMA, shared memory, IPC, memory hierarchy, cache behavior, and accelerator architectures.
  • Hands‑on experience with GPU architectures and parallel computing.
  • Experience with Vulkan, OpenCL, OpenGL ES, Vulkan Compute, OpenVX, or equivalent technologies.
  • Experience profiling and optimizing system performance using tracing, logging, and debugging tools.
  • Linear Algebra: vectors, matrices, tensors, transformations, projections, eigenvalues/eigenvectors, matrix decompositions, numerical linear algebra.
  • Geometry & Robotics Mathematics: coordinate transformations, homogeneous transforms, rotation matrices, quaternions, kinematics, dynamics, trajectory generation.
  • Optimization & Estimation: multivariable calculus, probability, statistics, numerical optimization, Kalman filtering, state estimation, nonlinear optimization.
  • AI Computing Fundamentals: understanding of…
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