Senior Staff AI/ML & GPU Performance Validation Engineer

WHAT YOU DO AT AMD CHANGES EVERYTHING At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career. THE ROLE: We are seeking a highly experienced Senior Staff Engineer to lead and drive test development, performance benchmarking, and validation for AI/ML frameworks, AI models, and AI agent-based systems on GPU platforms. This role requires deep expertise in GPU performance analysis, AI/ML training and inference frameworks, strong understanding of CPU/GPU hardware components, and leadership in building scalable automation and CI/CD solutions across bare-metal and virtualized environments. Key Responsibilities Design, develop, and own test and validation frameworks for AI/ML frameworks, AI models, AI agents and HPC focusing on GPU performance, correctness, and scalability Lead GPU performance benchmarking for AI/ML training, inference, and agent-based and HPC workloads Develop and maintain performance baselines and regression detection across multiple GPU and CPU platforms Analyze and debug performance, functional, and stability issues spanning hardware, drivers, runtime, frameworks, and models Build automated test pipelines covering bare-metal and virtualized environments (VMs, containers) Drive CI/CD integration for large-scale AI/ML validation infrastructure Collaborate closely with AI framework, model, compiler, OS, driver, and hardware teams Mentor senior engineers and provide technical leadership across cross-functional teams Influence long-term strategy for AI/ML performance validation and system-level testing Required Qualifications Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field (or equivalent experience) 12+ years of industry experience in test development, performance engineering, or systems validation Deep understanding of GPU and CPU architecture and hardware components, including memory hierarchy, interconnects, and compute pipelines Strong experience with AI/ML frameworks (e.g., PyTorch, TensorFlow, JAX, ONNX Runtime) Hands-on experience with AI model training and inference , including large-scale models Experience working with AI agents and agent-based workflows Proven expertise in GPU performance benchmarking, profiling, and root-cause analysis Strong debugging skills across hardware, firmware, drivers, runtime, and application layers Proficiency in Python, C/C++, or similar languages Experience building automation frameworks and integrating them into CI/CD pipelines Experience working in virtualization environments (containers, VMs) Preferred Qualifications Experience validating LLMs, multimodal models, or autonomous AI agents Knowledge of CUDA, ROCm, or other GPU programming ecosystems Experience with distributed training and inference Familiarity with GPU/CPU performance tools (e.g., Nsight, ROCm tools, perf, VTune, custom profilers) Background working closely with gpu silicon, compiler, or systems software teams #LI-TC1 #LI-HYBRID Benefits offered are described: AMD benefits at a glance. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process. AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here. This posting is for an existing vacancy.

Benefits offered are described: AMD benefits at a glance. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process. AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here. This posting is for an existing vacancy.

THE ROLE: We are seeking a highly experienced Senior Staff Engineer to lead and drive test development, performance benchmarking, and validation for AI/ML frameworks, AI models, and AI agent-based systems on GPU platforms. This role requires deep expertise in GPU performance analysis, AI/ML training and inference frameworks, strong understanding of CPU/GPU hardware components, and leadership in building scalable automation and CI/CD solutions across bare-metal and virtualized environments. Key Responsibilities Design, develop, and own test and validation frameworks for AI/ML frameworks, AI models, AI agents and HPC focusing on GPU performance, correctness, and scalability Lead GPU performance benchmarking for AI/ML training, inference, and agent-based and HPC workloads Develop and maintain performance baselines and regression detection across multiple GPU and CPU platforms Analyze and debug performance, functional, and stability issues spanning hardware, drivers, runtime, frameworks, and models Build automated test pipelines covering bare-metal and virtualized environments (VMs, containers) Drive CI/CD integration for large-scale AI/ML validation infrastructure Collaborate closely with AI framework, model, compiler, OS, driver, and hardware teams Mentor senior engineers and provide technical leadership across cross-functional teams Influence long-term strategy for AI/ML performance validation and system-level testing Required Qualifications Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field (or equivalent experience) 12+ years of industry experience in test development, performance engineering, or systems validation Deep understanding of GPU and CPU architecture and hardware components, including memory hierarchy, interconnects, and compute pipelines Strong experience with AI/ML frameworks (e.g., PyTorch, TensorFlow, JAX, ONNX Runtime) Hands-on experience with AI model training and inference , including large-scale models Experience working with AI agents and agent-based workflows Proven expertise in GPU performance benchmarking, profiling, and root-cause analysis Strong debugging skills across hardware, firmware, drivers, runtime, and application layers Proficiency in Python, C/C++, or similar languages Experience building automation frameworks and integrating them into CI/CD pipelines Experience working in virtualization environments (containers, VMs) Preferred Qualifications Experience validating LLMs, multimodal models, or autonomous AI agents Knowledge of CUDA, ROCm, or other GPU programming ecosystems Experience with distributed training and inference Familiarity with GPU/CPU performance tools (e.g., Nsight, ROCm tools, perf, VTune, custom profilers) Background working closely with gpu silicon, compiler, or systems software teams #LI-TC1 #LI-HYBRID