Staff Engineer, Software – Physical AI

Posted 5 Days Ago
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Farmington Hills, MI, USA
In-Office
Senior level
3D Printing
The Role
Leads Physical AI and robotics software initiatives using Renesas R-Car SoCs. Develops reference platforms, integrates and debugs embedded Linux, ROS2, AI runtimes, drivers, firmware, and heterogeneous accelerators. Optimizes perception, sensor fusion, SLAM, planning, control, and inference workloads across CPU, GPU, NPU, DSP, and dedicated hardware. Provides customer-facing technical leadership, performance modeling, architecture reviews, proof-of-concept development, and requirements definition for future SoCs and robotic platforms.
Summary Generated by Built In
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 how GEMM, convolution, attention, tensor transformations, interpolation, and other mathematical operators map onto CPU/GPU/NPU hardware.
  • Ability to analyze computational complexity, memory bandwidth requirements, accelerator utilization, and data movement characteristics of AI and robotics workloads.
  • Strong communication, customer-facing, and technical leadership skills

Preferred Qualifications

  • Experience with Renesas R-Car or comparable high-performance SoCs.
  • Strong experience with ROS2 and robotics middleware.
  • Experience developing humanoid robots, autonomous mobile robots, robotic manipulators, or other Physical AI systems.
  • Experience with perception, sensor fusion, localization, SLAM, navigation, planning, and control algorithms.
  • Experience with AI frameworks such as PyTorch, TensorFlow, ONNX, and OpenCV.
  • Experience optimizing AI models for embedded deployment.
  • Experience with robotic simulation environments such as Isaac Sim, Gazebo, MuJoCo, or equivalent.
  • Experience with Physical AI, foundation models, reinforcement learning, vision-language-action models, or embodied AI systems.
  • Experience integrating sensors including cameras, LiDAR, radar, IMUs, encoders, and force/torque sensors.
  • Experience with PowerVR or comparable embedded GPU architectures.

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?

Renesas Electronics is an equal opportunity and affirmative action employer, committed to supporting diversity and fostering a work environment free of discrimination on the basis of sex, race, religion, national origin, gender, gender identity, gender expression, age, sexual orientation, military status, veteran status, or any other basis protected by law. For more information, please read our Diversity & Inclusion Statement.

Renesas Electronics deals with dual-use technology that is subject to U.S. export controls regulations. Under these regulations it may be necessary for Renesas to obtain U.S. government export license prior to release of technology to certain persons. The decision whether or not to file or pursue an export license application is at the sole discretion of Renesas.

Skills Required

  • BS, MS, or PhD in Computer Engineering, Electrical Engineering, Computer Science, Robotics, Applied Mathematics, or a related field
  • 5+ years of experience in embedded systems, semiconductor application engineering, robotics, AI, autonomous systems, or high-performance computing 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
  • Knowledge of linear algebra, including vectors, matrices, tensors, transformations, projections, eigenvalues, eigenvectors, matrix decompositions, and numerical linear algebra
  • Knowledge of robotics mathematics, including coordinate transformations, homogeneous transforms, rotation matrices, quaternions, kinematics, dynamics, and trajectory generation
  • Knowledge of optimization and estimation, including multivariable calculus, probability, statistics, numerical optimization, Kalman filtering, state estimation, and nonlinear optimization
  • Understanding of AI computing fundamentals and mapping GEMM, convolution, attention, tensor transformations, and interpolation to CPU, GPU, and NPU hardware
  • Ability to analyze computational complexity, memory bandwidth, accelerator utilization, and data movement characteristics of AI and robotics workloads
  • Strong communication, customer-facing, and technical leadership skills
  • Experience with Renesas R-Car or comparable high-performance SoCs
  • Strong experience with ROS2 and robotics middleware
  • Experience developing humanoid robots, autonomous mobile robots, robotic manipulators, or other Physical AI systems
  • Experience with perception, sensor fusion, localization, SLAM, navigation, planning, and control algorithms
  • Experience with PyTorch, TensorFlow, ONNX, and OpenCV
  • Experience optimizing AI models for embedded deployment
  • Experience with Isaac Sim, Gazebo, MuJoCo, or equivalent robotic simulation environments
  • Experience with Physical AI, foundation models, reinforcement learning, vision-language-action models, or embodied AI systems
  • Experience integrating cameras, LiDAR, radar, IMUs, encoders, and force/torque sensors
  • Experience with PowerVR or comparable embedded GPU architectures

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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