Staff Engineer, Software – Physical AI - Farmington Hills, United States
Originally posted 7 October 2026 by the employer.
Drive customer adoption of Renesas R-Car SoCs for robotic and Physical AI platforms.
About the role
This role drives customer and ecosystem adoption of Renesas R-Car SoCs for robotic and Physical AI platforms. You will provide technical leadership for humanoid robots, autonomous systems, and embodied AI based on R-Car SoCs.
What you'll do
- Serve as technical lead for Physical AI, humanoid robotics, autonomous systems, and robotic compute platforms.
- 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.
What you'll need
- 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.
- Experience with Linear Algebra (vectors, matrices, tensors, transformations, projections, eigenvalues/eigenvectors, matrix decompositions, numerical linear algebra).
- Experience with Geometry & Robotics Mathematics (coordinate transformations, homogeneous transforms, rotation matrices, quaternions, kinematics, dynamics, trajectory generation).
- Experience with Optimization & Estimation (multivariable calculus, probability, statistics, numerical optimization, Kalman filtering, state estimation, nonlinear optimization).
- Understanding of AI Computing Fundamentals: how GEMM, convolution, attention, tensor transformations, interpolation, and other mathematical operators map onto CPU/GPU/NPU hardware.
Nice to have
- 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.
Skills: R-Car SoCs, robotics, AI runtimes, GPU/NPU accelerators, device drivers, Linux kernel
This role has been open 8 days — well below the 85-day median for Infrastructure/Platform Software roles.
Infrastructure/Platform Software · Systems Software
|
Open roles in category
33
|
Median days open
85 d
|
Median salary
$269k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Renesas Electronics | All employers we track in this specialty (33 roles · 20 employers) |
|---|---|---|
| Open roles in this specialty | 1 | 33 |
| Open roles in the wider Software, Firmware & Systems family | 125 | 6156 · 145 employers |
| Median days open | 8 d | 85 d (−77 d vs this employer) |
| Median salary (USD postings) | — | $269k |
Skills observed across this category: R-Car SoCs, robotics, AI runtimes, GPU/NPU accelerators, device drivers, Linux kernel
Who's hiring in this category
- NVIDIA · 7 open roles · median 85 d
- Qualcomm · 4 open roles · median 108 d
- Cerebras · 2 open roles · median 58 d
- GlobalFoundries · 2 open roles · median 44 d
- MatX · 2 open roles · median 152 d
- Teradyne · 2 open roles · median 131 d
How we counted: 33 open Infrastructure/Platform Software (Systems Software) roles from 20 employers tracked in the SemiconductorJobs index, counted 16 Oct 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Software, Firmware & Systems family row. Figures refresh nightly.