AMD develops processors, graphics, and adaptive computing technologies that support healthcare, scientific discovery, artificial intelligence, and other applications. The AI Applications Engineer will develop AI-assisted workflows for FPGA and SoC reference designs, optimize open-source models and inference workloads across hardware platforms, and research AI infrastructure security. The role also involves technical content creation, prototyping, benchmarking, and collaboration with engineering, product, field, and customer teams.
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
Qualification
Required
• 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
Preferred
• 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
Benefits
Hybrid work environment
Advanced Micro Devices is a semiconductor company that designs and develops graphics units, processors, and media solutions.
