Senior Staff Engineer, SoC Application Engineering

The High Performance Compute (HPC) SoC Business Division is seeking a Senior Staff Engineer, SoC Application Engineering – Robotics & GPU to provide technical leadership for customer and partner development using the Renesas R-Car SoC family.

This position will play an integral role in the global effort to position Renesas as the premier semiconductor partner for humanoid robot subsystems
, winning design-ins at strategic accounts, distribution partners, and mass‑market customers through targeted engineering, optimized AI solutions and workflows, and strategic ecosystem partnerships.

A primary focus of this role will be enabling the brain, AI, perception, compute, and control functionality of humanoid and advanced robotic platforms using R-Car So Cs .

The successful candidate will combine strong embedded SoC expertise with hands‑on experience in robotics, GPU and heterogeneous compute, AI workloads, system‑level debugging, and performance optimization
.

• Act as a senior technical lead for R-Car based humanoid robotics, physical AI, autonomous systems, and advanced robotic platforms
  .
• Lead collaboration with the Physical AI & Humanoid Lab to develop robotic platforms, prototypes, proof‑of‑concepts, and demonstrations.
• Lead ecosystem partner project execution to develop robotic reference designs and reusable customer solutions.
• Support customer and partner programs from architecture and platform bring‑up through software integration, debugging, performance optimization, validation, and production.
• Lead root‑cause analysis of complex hardware/software issues across:
  • Linux/Ubuntu
  • ROS2 and robotics middleware
  • GPU and AI accelerators
  • Device drivers and firmware
  • Memory management and SMMU/IOMMU
  • IPC and heterogeneous multicore systems
  • AI runtimes and inference pipelines
  • System performance, latency, and memory bandwidth
• Analyze customer robotic architectures and requirements against R-Car capabilities and identify technical gaps, risks, and recommended solutions.
• Support customer RFI/RFQ activities, architecture reviews, design reviews, and technical debug sessions
  .
• Develop robotic proof‑of‑concepts, demonstrations, reference applications, and benchmarks showcasing R-Car SoC capabilities.
• Provide technical expertise in GPU compute and heterogeneous processing
  , including CPU/GPU/NPU workload partitioning, synchronization, memory movement, and performance optimization.
• Support GPU and compute technologies such as Vulkan, Vulkan Compute, OpenCL, OpenGL ES, and OpenVX
  .
• Analyze and optimize system performance across CPU, GPU, NPU, DSP, memory, and other hardware accelerators.
• Support robotic workloads including perception, sensor fusion, localization, mapping, motion planning, navigation, manipulation, and AI inference
  .
• Work with Renesas global engineering teams, customers, and ecosystem partners to define requirements for future R-Car SoCs, AI software, tools, and robotic reference platforms.

• Bachelor's, Master's, or Ph.D. degree in Computer Engineering, Electrical Engineering, Computer Science, Robotics
  , or a related field.
• 10+ years of experience in embedded systems, semiconductor application engineering, robotics, automotive electronics, or related fields.
• Strong embedded development and debugging experience using C and C++.
• Deep understanding of embedded SoC architecture, including CPU, GPU, memory, firmware, operating systems, drivers, middleware, and hardware accelerators.
• Strong hands‑on experience with embedded Linux and complex system‑level debugging.
• Experience with BSPs, bootloaders, Linux kernel, device drivers, firmware, and user‑space applications.
• Strong understanding of heterogeneous multicore architectures, memory management, IPC, DMA, shared memory, and hardware accelerators.
• Hands‑on knowledge of GPU architecture and GPU compute
  .
• Experience with one or more of Vulkan, OpenCL, OpenGL ES, Vulkan Compute, or OpenVX
  .
• Experience with system and GPU performance analysis using tracing, profiling, logging, and debugging tools.
• Familiarity with embedded AI/ML workloads and deployment on heterogeneous SoCs.
• Strong problem‑solving, customer‑facing, and technical…