Senior AI Systems Performance Engineer

Advanced Micro Devices, Inc•Austin, TX

1d•Hybrid

About The Position

ADVANCE YOUR CAREER. ADVANCE THE WORLD. 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 AMD is shaping the future. Whether you’re designing 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. THE ROLE: As a Senior AI Systems Performance Engineer, you will serve as a technical leader responsible for defining and driving AMD's AI workload performance characterization strategy across next-generation embedded and client platforms. You will lead the development of benchmarking methodologies, analyze complex performance bottlenecks across hardware and software boundaries, and deliver strategic recommendations that influence silicon utilization, software optimization efforts, product planning decisions, and customer engagements. Working across multiple engineering organizations, you will help establish performance best practices while serving as a subject matter expert for AI performance analysis, platform optimization, and workload characterization. THE PERSON: The ideal candidate combines strong AI software knowledge with deep hardware and system-level expertise. You possess a strong understanding of modern AI workloads, platform architecture, performance engineering principles, and workload optimization techniques. You are comfortable working with senior technical leaders, product planners, executives, and customers, translating technical performance data into meaningful business and engineering insights. You excel at identifying root causes of performance issues, designing measurement methodologies, and influencing decision-making through data-driven analysis.

Requirements

Bachelor's or Master's degree in Computer Engineering, Electrical Engineering, Computer Science, or a related technical discipline.
This role is not eligible for visa sponsorship.

Nice To Haves

Deep understanding of AI inference workloads and performance optimization techniques.
Strong hands-on experience with AI frameworks such as PyTorch, ONNX Runtime, vLLM, TensorFlow, ROCm, Ryzen AI, or similar technologies.
Experience analyzing and optimizing performance of LLMs, VLMs, multimodal workloads, computer vision applications, and generative AI systems.
Advanced knowledge of Linux systems, performance analysis, and debugging methodologies.
Strong understanding of AMD APUs, GPUs, CPUs, NPUs, unified memory architectures, or similar heterogeneous computing platforms.
Experience utilizing low-level profiling, tracing, power analysis, and performance characterization tools.
Extensive experience with BIOS configuration, platform tuning, and system optimization techniques.
Demonstrated ability to communicate complex technical findings to executives, customers, product teams, and senior engineering leadership.
Experience supporting customer-facing performance discussions, technical reviews, or competitive benchmarking initiatives.
Strong scripting and automation skills using Python, Shell, or similar technologies.

Responsibilities

Lead AI workload benchmarking and performance characterization efforts across AMD AI-enabled embedded and client platforms.
Design and maintain scalable benchmarking infrastructure, automated performance dashboards, and workload analysis methodologies.
Drive deep root-cause analysis of performance bottlenecks across software, firmware, operating system, silicon, memory, and platform layers.
Utilize advanced profiling and tracing tools to characterize AI workload behavior and identify optimization opportunities.
Analyze power, performance, throughput, latency, and efficiency tradeoffs across diverse AI deployments.
Collaborate closely with architecture, firmware, software, platform, and product teams to influence optimization strategies and future product direction.
Provide actionable performance insights to engineering leadership, business teams, product planning organizations, and external partners.
Support customer-facing performance investigations and technical engagements when required.
Develop performance evaluation methodologies used for competitive analysis and business strategy.
Mentor junior engineers and help establish best practices across the AI performance engineering organization.