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Physical AI, Computer Vision Engineer

AMD· Engineering
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Hybrid (Austin, TX), Hybrid (Novi, MI), Hybrid (San Jose, CA)$174.4kFull-timePosted 3mo ago

About the role

Senior Physical AI Software Engineer role focused on designing, developing, and optimizing embedded software for AI-enabled edge systems across embedded Linux and RTOS, with expertise in computer vision, AI inference, sensor processing, and real-time performance.

Responsibilities

  • Design, develop, and maintain embedded software for AI-enabled edge computing platforms.
  • Develop software for Linux and Real-Time Operating Systems (RTOS) supporting deterministic, low-latency execution.
  • Design and implement real-time software for perception, sensor processing, control, and autonomous decision-making.
  • Develop and integrate computer vision, image processing, and AI inference applications for real-world deployment.
  • Build and optimize high-performance image, video, and sensor processing pipelines.
  • Optimize software across heterogeneous computing architectures including CPUs, GPUs, FPGAs, and AI accelerators.
  • Collaborate with AI, FPGA, hardware, systems, and platform teams to deliver integrated Physical AI solutions.
  • Support platform bring-up, debugging, validation, and system integration.
  • Analyze and optimize latency, throughput, memory utilization, power efficiency, and overall system performance.
  • Contribute to software architecture, technical documentation, coding standards, and engineering best practices.
  • Develop demonstrations, reference applications, and customer enablement solutions showcasing AMD embedded technologies.

Qualifications

  • Experience with RTOS platforms such as QNX, GreenHills, or similar real-time operating systems.
  • Experience designing software for low-latency, safety-critical, or time-sensitive embedded applications.
  • Experience with AMD Vitis AI or equivalent AI deployment frameworks.
  • Experience with AMD Ryzen Embedded, EPYC Embedded, Versal AI Edge, Zynq UltraScale+, Kria, or similar edge computing platforms.
  • Understanding of FPGA-based acceleration and hardware/software co-design methodologies.
  • Experience with AI inference deployment using ONNX, PyTorch, TensorFlow, or related frameworks.
  • Experience with ROS 2 and robotics software architectures.
  • Understanding of perception systems including cameras, radar, lidar, and sensor fusion technologies.
  • Familiarity with graphics and visualization technologies such as OpenGL, Vulkan, or Wayland.
  • Experience with Linux kernel, BSP, device driver, or low-level platform software development.
  • Understanding of heterogeneous computing architectures combining CPUs, GPUs, FPGAs, and dedicated AI accelerators.
  • Experience with performance profiling, optimization, and benchmarking on multicore systems.
  • Knowledge of networking, middleware, and distributed edge computing systems.
  • Experience within robotics, automotive, industrial automation, aerospace, machine vision, or related embedded systems domains.

Skills

Required:Embedded software developmentReal-Time Operating Systems (RTOS)Computer visionAI inference frameworksHeterogeneous computing

Benefits

  • AMD benefits at a glance
Last updated Oct 22, 2026. Interested? Apply on the company site.
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