AI Applications Engineer

Advanced Micro Devices, Inc•San Jose, CA

6d•Hybrid

About The Position

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.

Requirements

Bachelors or Masters degree in Electrical Engineering, Mathematics, Computer Science, Engineering, or an equivalent
Proficiency in Python or C/C++
Linux development environments
Git-based version control

Nice To Haves

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.
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.

Responsibilities

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.