THE ROLEAMD is seeking an experienced FPGA/Adaptive SoC Applications Design Engineer to help define and develop next-generation Physical AI platforms built on AMD Adaptive SoCs, Ryzen™ AI Embedded processors, and AMD FPGA technologies.
In this role, you will work at the intersection of hardware, embedded software, and AI acceleration to develop reference designs, proof-of-concepts, and customer solutions that enable intelligent robotics, industrial automation, autonomous machines, smart vision systems, and edge AI applications.
Working alongside AMD architecture, silicon engineering, software, and product teams, you will help customers transform innovative ideas into production-ready solutions while influencing future AMD products through real-world application experience.
THE PERSONThe ideal candidate is passionate about solving complex system-level challenges using programmable logic and heterogeneous compute architectures. You enjoy working across hardware and software boundaries, are comfortable bringing up new platforms, and thrive in customer-facing technical environments.
You are naturally curious, enjoy learning emerging technologies, and possess the communication skills needed to collaborate effectively with customers, ecosystem partners, and engineering teams across AMD.
KEY RESPONSIBILITIES- Design and develop FPGA and Adaptive SoC solutions for Physical AI applications including robotics, industrial automation, autonomous systems, and intelligent edge devices.
- Create reference architectures, demonstration platforms, and proof-of-concept designs showcasing AMD Adaptive SoC and Ryzen AI Embedded technologies.
- Develop FPGA RTL, AI Engine, HLS, and embedded software components using AMD Vivado™, Vitis™, and Yocto development environments.
- Integrate high-speed interfaces including PCIe®, Ethernet, DisplayPort™, MIPI CSI/DSI, USB, CAN, and industrial communications.
- Develop sensor processing pipelines incorporating cameras, radar, LiDAR, IMUs, and other edge sensing technologies.
- Collaborate with AMD architecture, silicon, software, and AI engineering teams to influence future product capabilities and improve customer experience.
- Support board bring-up, silicon validation, hardware debugging, and system performance optimization on next-generation AMD platforms.
- Work closely with strategic customers and ecosystem partners to accelerate deployment of innovative Physical AI solutions.
- Investigate complex hardware and software issues, identify root causes, and deliver robust technical solutions.
- Stay current with emerging trends in AI, robotics, machine vision, embedded computing, FPGA development, and heterogeneous computing architectures.
PREFERRED EXPERIENCE- Experience developing FPGA designs using Verilog, SystemVerilog, or VHDL.
- Experience with AMD Vivado, Vitis, Vitis HLS, AI Engine development, or comparable FPGA development environments.
- Strong embedded software development skills using C/C++.
- Experience with Embedded Linux, Yocto, RTOS, or bare-metal software development.
- Experience integrating hardware accelerators with embedded processors.
- Familiarity with AI inference acceleration, computer vision, sensor fusion, or robotics applications.
- Experience with high-speed digital interfaces including PCIe, Ethernet, Ethercat, USB, DisplayPort, MIPI, SPI, I²C, UART, and GPIO.
- Knowledge of robotics frameworks such as ROS 2 is advantageous.
- Experience with hardware debugging tools including JTAG, oscilloscopes, protocol analyzers, and logic analyzers.
- Familiarity with Git, CI/CD workflows, and modern software development practices.
- Strong analytical, debugging, and problem-solving skills.
- Excellent written and verbal communication skills with the ability to present complex technical concepts to customers and internal stakeholders.
DESIRABLE EXPERIENCE- Industrial automation or robotics.
- Low Latency High Performance Motor Control
- DSP Algorithm Deployment and modelling
- Autonomous mobile robots (AMRs) or autonomous vehicles.
- Functional safety or real-time embedded systems.
- AI model deployment on edge devices.
- Computer vision or machine learning acceleration.
- Multi-sensor fusion systems.
- Hardware/software co-design.
- Customer-facing applications engineering or technical consulting.
ACADEMIC CREDENTIALSBachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, Robotics Engineering, or a related technical discipline.
LOCATIONSan Jose, CA or Austin, TX
This role is not eligible for visa sponsorship.
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