Lead AI Power & Performance Engineer
AMD · Posted Nov 5
High-performance processors, graphics cards, data center solutions, and AI accelerators
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About the role
AMD's AI System Power and Performance team evaluates, benchmarks, profiles, and optimizes AI inference workloads across modern CPU, GPU, APU, NPU, and heterogeneous computing platforms. The role sits at the intersection of AI frameworks and inference runtimes (PyTorch, ONNX Runtime, vLLM, llama.cpp, TensorFlow), platform architecture, and system-level power and performance analysis. This senior technical lead will independently drive benchmarking strategy, competitive evaluation, root-cause analysis, and technical recommendations while collaborating with engineering, product, customer, and executive stakeholders.
What you will do
- Define and drive the AI performance benchmarking and workload characterization strategy across CPU, GPU, APU, NPU, and heterogeneous platforms.
- Benchmark AI inference workloads using PyTorch, ONNX Runtime, vLLM, llama.cpp, TensorFlow, and related frameworks and runtimes.
- Analyze key performance metrics, including latency, throughput, time to first token, tokens per second, memory utilization, power consumption, and performance per watt.
- Profile workloads and identify bottlenecks across AI frameworks, runtimes, libraries, drivers, operating systems, firmware, memory subsystems, and hardware.
- Lead complex root-cause analysis and recommend optimizations related to quantization, graph execution, kernels, memory usage, workload scheduling, and heterogeneous compute utilization.
- Conduct competitive benchmarking across AMD and competing CPU, GPU, APU, and AI accelerator platforms.
- Collaborate with SoC architects, framework, runtime, compiler, driver, firmware, and system software teams to improve AI workload performance.
- Develop and improve automation for benchmark execution, data collection, regression analysis, and results visualization.
- Translate benchmarking data into actionable technical recommendations that influence software optimization, hardware design, product strategy, and customer engagements.
- Present technical findings and recommendations to engineering teams, customers, executives, and other cross-functional stakeholders.
- Provide technical leadership, mentor engineers, and drive alignment across multiple teams.
Skills used in this role
What the employer is looking for
- 10 to 14+ years of relevant experience in AI performance engineering, system performance analysis, workload optimization, benchmarking, or post-silicon performance validation.
- Hands-on experience evaluating, benchmarking, and characterizing AI inference workloads on CPU, GPU, APU, NPU, or heterogeneous computing platforms.
- Strong experience with PyTorch, ONNX Runtime, vLLM, llama.cpp, TensorFlow, or equivalent AI frameworks and inference runtimes.
- Deep expertise in platform architecture, hardware performance, and system-level optimization, including CPU, GPU, NPU, memory, power, and thermal subsystems.
- Strong Linux systems expertise, including performance profiling, workload tracing, memory management, workload scheduling, automation, and system-level debugging.
- Experience with profiling tools such as Linux perf, AMD uProf, ROCm Profiler, Nsight Systems, VTune, Perfetto, or equivalent tools.
- Strong understanding of hardware architecture, memory hierarchy, data movement, power and thermal behavior, and performance trade-offs.
- Experience with AI optimization techniques such as quantization, mixed-precision inference, graph optimization, operator fusion, kernel tuning, and memory optimization.
- Proficiency in Python and Bash for benchmark automation, data analysis, and reporting.
- Working knowledge of C or C++ for performance debugging and low-level workload analysis.
- Ability to independently drive benchmarking strategy, competitive analysis, root-cause investigation, and technical recommendations.
- Excellent executive, customer-facing, and cross-functional communication skills.
- Ability to convert complex performance data into clear technical reports, dashboards, presentations, and actionable recommendations.
- Proven ability to provide technical leadership and drive complex initiatives across multiple engineering teams.
- Bachelor’s or master’s degree in Computer Engineering, Electrical Engineering, Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
Preferred qualifications
- Experience with ROCm, Ryzen AI Software, Vitis AI, MIGraphX, or related AI technologies.
- Experience with MLPerf Inference or comparable AI benchmarking methodologies.
- Knowledge of INT8, INT4, FP16, BF16, and mixed-precision execution.
- Experience with large language model inference, including batching, KV-cache management, model parallelism, and memory optimization.
- Experience with Docker, virtualization, and containerized AI environments.
- Exposure to post-silicon bring-up, early silicon testing, competitive benchmarking, or customer-facing performance analysis.
- Experience influencing platform architecture, software roadmaps, product strategy, or customer solutions through data-driven performance analysis.
Benefits and support
- Compensation and benefits are detailed in the job posting
About AMD
AMD is a global semiconductor company that designs high-performance central processing units (CPUs), graphics processing units (GPUs), and adaptive processors for data centers, personal computers, gaming consoles, and embedded systems. The company specializes in advanced computing solutions and AI accelerators, positioning itself as a major leader in modern high-performance and artificial intelligence hardware. Through strategic developments and acquisitions, AMD continues to expand its ecosystem across cloud infrastructure, enterprise computing, and physical AI.
- Industry
- Semiconductors
- Company size
- 31000 employees
- Founded
- 1969-05-01
- Location
- Santa Clara, California, USA
- Funding stage
- Public Company
Funding
Public Company
- 2007-11-16Post Ipo
Leadership
Chair and Chief Executive Officer
Executive Vice President, Chief Financial Officer and Treasurer
Executive Vice President and Chief Technology Officer
Executive Vice President and Chief Commercial Officer
Executive Vice President and General Manager, Data Center Solutions Business Group
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