Embedded Software Engineer - Physical AI
AMD
- Location
- San Jose, California
- Employment
- Full Time
- Work model
- On-Site
- Level
- Mid
Skills
About this role
WHAT YOU DO AT AMD CHANGES EVERYTHING At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.
THE ROLE
AMD is seeking an experienced Embedded Software Engineer to help develop next-generation Physical AI platforms powered by AMD Adaptive SoCs and Ryzen™ AI Embedded processors. Working at the intersection of embedded software, computer vision, graphics, and edge AI, you will help bring intelligent robotics, industrial automation, autonomous systems, and smart vision applications to life. In partnership with AMD architecture, silicon, AI, and product teams, you will develop reference platforms, proof-of-concepts, and next-generation solutions that showcase AMD technology in real-world deployments. Join a team shaping the future of Physical AI through adaptive computing. You'll work with industry-leading Adaptive SoC, FPGA, and AI technologies, collaborate with world-class engineers, and help enable the next generation of intelligent machines that are transforming industries worldwide. THE PERSON You are passionate about building robust embedded software and solving complex system-level challenges. You enjoy working across hardware and software boundaries, bringing up new platforms, and developing innovative solutions in vision, graphics, and AI. You thrive in collaborative environments, are naturally curious, and enjoy learning new technologies while partnering across engineering disciplines to deliver impactful products.
KEY RESPONSIBILITIES
Develop embedded C/C++ software and Linux platform support (BSP/Yocto) for Physical AI platforms built on AMD Adaptive SoCs and Ryzen™ AI Embedded processors. Build and optimize computer vision and camera processing pipelines, including sensor drivers, MIPI CSI integration, ISP tuning, and image/video processing frameworks. Develop graphics and display software, including display pipeline bring-up, GPU-accelerated rendering, and visualization solutions for intelligent edge applications. Deploy and optimize edge AI inference models and runtime environments utilizing available NPU, GPU, and heterogeneous compute resources. Lead platform bring-up, hardware/software integration, driver development, low-level debugging, and system validation activities. Collaborate with AMD architecture, silicon, AI, and product engineering teams to influence future platform capabilities and improve the developer experience. Support performance optimization, system characterization, and software enablement for next-generation AMD platforms. Investigate complex hardware and software issues, identify root causes, and deliver robust technical solutions. Contribute to reference platforms, proof-of-concepts, and customer-facing demonstrations that showcase AMD technologies in robotics, industrial automation, computer vision, and Physical AI applications.
PREFERRED EXPERIENCE
Embedded software development using C/C++, Python, automation, and AI model workflows. Experience with Embedded Linux, Yocto, BSP development, device drivers, RTOS, or bare-metal software development. Experience with computer vision and camera pipelines, including MIPI CSI, ISP tuning, V4L2, OpenCV, or GStreamer. Experience with graphics and display software, including DisplayPort, MIPI DSI, display drivers, compositors, EGL, OpenGL, or Vulkan. Experience deploying and optimizing edge AI