Integration Engineer - Perception and Platform

Advanced Micro Devices, Inc•San Jose, CA

5d•Hybrid

About The Position

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. Our Physical AI team develops technologies that enable machines to perceive, reason, and act in the physical world. By combining AI, embedded computing, robotics, perception systems, and adaptive computing platforms, we create solutions that bridge the gap between digital intelligence and real-world interaction. Our work spans robotics, automotive, industrial automation, and emerging intelligent edge applications. We are seeking a Senior Software Engineer to join our Physical AI team, developing next-generation AI-enabled systems for automotive, robotics, and intelligent edge applications. This role focuses on the deployment and optimization of advanced perception, computer vision, and AI workloads on high-performance adaptive computing platforms, including AMD Versal™ AI Edge Gen 2 devices. Working at the intersection of AI, robotics, embedded systems, and accelerated computing, you will help build intelligent systems capable of understanding and interacting with the physical world in real time.

Requirements

Strong software development experience in C++, Python, and Linux environments.
Experience deploying and optimizing machine learning or deep learning models for edge devices.
Strong understanding of AI inference pipelines and performance optimization techniques.
Experience with computer vision, perception systems, or sensor processing applications.
Solid understanding of embedded systems and heterogeneous computing architectures.
Experience profiling and optimizing software performance across CPU, GPU, NPU, FPGA, or accelerator-based systems.
Strong debugging, problem-solving, and system integration skills.
Excellent written and verbal communication skills.
Ability to work effectively within multidisciplinary engineering teams.

Nice To Haves

Experience with AMD Vitis AI or equivalent AI deployment frameworks.
Experience with AMD Versal AI Edge, Zynq UltraScale+, Kria, or other adaptive computing platforms.
Understanding of FPGA acceleration and hardware/software co-design methodologies.
Experience developing AI applications using ONNX, PyTorch, TensorFlow, or similar frameworks.
Familiarity with quantization, model optimization, pruning, and edge deployment techniques.
Experience with ROS 2 and robotics software architectures.
Understanding of perception systems including camera, radar, lidar, and sensor fusion pipelines.
Experience with graphics, visualization, or accelerated rendering technologies.
Familiarity with OpenGL, Vulkan, Wayland, or embedded graphics frameworks.
Experience with Linux kernel, device drivers, or low-level platform software development.
Experience with distributed AI, edge-to-cloud architectures, or heterogeneous computing systems.
Experience with robotics, automotive, aerospace, industrial automation, or other intelligent edge domains.

Responsibilities

Design, develop, and optimize software for Physical AI applications targeting AMD adaptive computing platforms.
Deploy and optimize AI inference workloads using Vitis AI and related toolchains.
Develop advanced perception pipelines for robotics, automotive, and intelligent edge applications.
Integrate AI models into high-performance embedded and edge computing environments.
Collaborate with hardware, FPGA, systems, and AI engineering teams to maximize application performance and efficiency.
Analyze and optimize end-to-end system performance, latency, throughput, and power consumption.
Support the development of computer vision, sensor fusion, and multimodal AI applications.
Develop and maintain software frameworks, SDKs, demonstrations, and reference implementations.
Contribute to technical documentation, best practices, and customer enablement activities.
Evaluate emerging AI models, frameworks, and deployment methodologies for Physical AI applications.