Software Engineer - Autonomy and Vision Systems

AMD AMD · Semiconductors · Austin, TX · Engineering

Software Engineer role focused on developing and integrating embedded software, computer vision, and real-time processing pipelines for intelligent systems in robotics, automotive, industrial, and edge AI applications. The role involves optimizing software for various AMD computing architectures, including embedded x86, adaptive SoCs, and AI-accelerated edge devices, with a strong emphasis on deterministic performance and low latency.

What you'd actually do

  1. Design, develop, and maintain software for embedded and edge computing platforms.
  2. Develop software for Linux and Real-Time Operating System (RTOS) environments.
  3. Design and implement real-time software components where deterministic performance and low latency are critical.
  4. Develop and integrate computer vision and perception applications for real-world deployment.
  5. Build and optimize image processing, video processing, and AI inference pipelines.

Skills

Required

  • Strong software development experience using C/C++.
  • Experience developing software within Linux environments.
  • Experience working with Real-Time Operating Systems (RTOS).
  • Understanding of RTOS concepts including task scheduling, inter-process communication, synchronization mechanisms, interrupt handling, and deterministic system behavior.
  • Understanding of embedded systems architecture and software development.
  • Experience developing software for embedded Linux platforms based on x86 and/or ARM architectures.
  • Experience developing or integrating computer vision, image processing, or video processing applications.
  • Familiarity with OpenCV or equivalent computer vision frameworks.
  • Understanding of system-level performance optimization on modern multicore processors.
  • Experience debugging and optimizing complex software systems.
  • Strong problem-solving and analytical skills.
  • Excellent written and verbal communication skills.
  • Ability to work effectively within multidisciplinary engineering teams.

Nice to have

  • 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 sys

What the JD emphasized

  • real-time
  • deterministic performance
  • low latency
  • embedded
  • edge computing

Other signals

  • develops technologies that enable machines to perceive, understand, and interact with the physical world
  • develops next-generation intelligent systems for robotics, automotive, industrial, and edge AI applications
  • real-time processing pipelines that enable machines to perceive and interact with the physical world
  • AI-enabled workloads
  • AI inference pipelines