AI Applications Engineer

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At AMD, we believe technology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMDis shapingthefuture.

Whether you’redesigning next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger— technology that moves the world forward.

Join us and, together, we’ll advance your career.

We are seeking an AI Applications Engineer to join AMD's Wired and Wireless Business Team within the Adaptive and Embedded Computing Group (AECG). This early-career role offers the opportunity to develop deep expertise at the intersection of artificial intelligence, FPGA/SoC design, embedded systems, and AI infrastructure security.

In this role, you will leverage AI technologies to accelerate the development, verification, and optimization of FPGA-based reference designs using AMD Vivado™ and Vitis™ tool flows. You will also contribute to strategic initiatives focused on AI infrastructure security, customization of open-source AI models, and efficient deployment of AI inference workloads across FPGA SoCs, NPUs, and GPUs in wired and wireless communications environments.

The ideal candidate is passionate about applying AI to real-world engineering challenges and eager to expand their expertise across hardware and software domains. You bring a strong technical foundation in AI/ML, programming, and mathematical modeling, combined with a collaborative mindset and a willingness to learn emerging technologies.

You thrive in a fast-paced, innovative environment and embody AMD's culture of technical excellence, continuous learning, teamwork, humility, and inclusion.

• Develop and utilize AI-assisted workflows to accelerate the creation, validation, and optimization of FPGA and SoC reference designs.
• Apply AI tools and techniques to improve engineering productivity throughout design and verification processes.
• Fine-tune, evaluate, and optimize open-source AI models for embedded, edge, and security-focused applications.
• Implement and optimize AI inference solutions on FPGA SoCs, NPUs, and GPUs, balancing performance, latency, power consumption, and resource utilization.
• Research and prototype innovative solutions for securing AI infrastructure deployments in enterprise environments.
• Contribute to industry and open-source communities focused on AI, embedded computing, and security technologies.
• Generate technical content, benchmarks, proof-of-concepts, and recommendations that support product strategy and long-term technology roadmaps.
• Collaborate with engineering, product management, field teams, and customers through technical presentations and knowledge-sharing initiatives.

• Experience in AI/ML engineering, applied research, software productivity initiatives, or related technical fields.
• Hands-on experience with training, fine-tuning, quantization, and evaluation of open-source AI models.
• Strong understanding of machine learning fundamentals, neural networks, optimization techniques, probability, and statistics.
• Proficiency in Python or C/C++, Linux development environments, and Git-based version control.
• Familiarity with FPGA design methodologies, RTL development (Verilog/VHDL), High-Level Synthesis (HLS), or embedded systems development.
• Exposure to edge AI deployment, AI model optimization, AI infrastructure security, or hardware-accelerated computing is a plus.
• Interest in learning FPGA/SoC architectures, AI stack optimization, and hardware-level security technologies.

• Bachelors or Masters degree in Electrical Engineering, Mathematics, Computer Science, Engineering, or an equivalent

• San Jose, CA with a hybrid work environment.
• Approximately
  10% travel for industry conferences, customer engagements, and cross-functional collaboration activities.

This role is not eligible for visa sponsorship.

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