Senior Staff Engineer, SoC Application Engineering

Renesas Electronics•Plano, TX

4d•Remote

About The Position

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 SoCs. 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.

Requirements

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 communication skills.

Nice To Haves

Experience with Renesas R-Car or comparable high-performance SoCs.
Strong experience with Ubuntu Linux.
Hands-on experience with ROS2, including application development, integration, debugging, and deployment.
Experience developing or integrating humanoid robots, autonomous mobile robots, robotic manipulators, or other physical AI systems.
Experience with robotic perception, sensor fusion, localization, mapping, motion planning, navigation, or control.
Experience with Imagination/PowerVR or comparable embedded GPU architectures.
Experience with GPU profiling and system performance tools.
Experience with embedded AI frameworks and runtimes such as PyTorch, TensorFlow, ONNX, OpenCV, or vendor-specific AI SDKs.
Experience optimizing AI models and workloads for embedded inference.
Experience integrating robotic sensors including cameras, LiDAR, radar, IMUs, encoders, or force/torque sensors.
Experience developing robotic demonstrations, proof-of-concepts, reference platforms, or semiconductor reference designs.

Responsibilities

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.