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AMD Logo AMD · IT - Software Development

Data Center GPU Performance Attainment Lead

United States, Austin 178400.00 - 267600.00 USD / Year · Job Posted May 31, 2026
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Job Description

The successful candidate will assume responsibility for post-silicon activities related to performance characterization and optimization of AMD Datacenter products, spanning both single-node and multi-node deployments.

Job Responsibility

  • Develop and maintain automation frameworks for workload execution and performance data collection, enabling scalable and repeatable characterization across configurations
  • Become a key stakeholder in the product power and performance definition process, ensuring alignment between architectural goals and measured silicon performance
  • Develop, execute, and evolve performance characterization and optimization test plans across diverse usage scenarios, including High Performance Computing (HPC) and Machine Learning (ML) workloads
  • Drive performance attainment for both scale-up (intra-node) and scale-out (multi-node) configurations, including: Multi-GPU scaling efficiency within a node, Interconnect bandwidth utilization (e.g., XGMI / Infinity Fabric), Collective communication efficiency and communication-compute overlap, Workload scaling behavior (strong and weak scaling), Identification and mitigation of system-level bottlenecks across distributed environments
  • Analyze interactions between power management features and performance behavior, optimizing configurations to achieve the best performance and performance-per-watt tradeoffs
  • Identify architectural and system-level bottlenecks and develop strategies to stress, expose, and mitigate worst-case performance scenarios
  • Support prototyping and experimentation efforts to evaluate enhancements and new features that impact performance
  • Debug and troubleshoot system-level issues across hardware, firmware, and software stacks observed in lab and production test environments
  • Collaborate with cross-functional teams (architecture, firmware, drivers, platform, and workload teams) to drive root-cause analysis through to resolution and performance closure
  • Proactively drive continuous improvement of post-silicon performance methodologies, tools, and workflows

Requirements

  • Proven leadership skills with experience mentoring junior engineers, coordinating cross-functional teams, and driving complex performance characterization and optimization efforts across multiple locations
  • Strong programming skills, with preference for Python and experience with ML frameworks (e.g., TensorFlow or PyTorch)
  • Proficiency in C/C++, scripting (Shell), and familiarity with performance tooling and automation workflows
  • Strong understanding of computer architecture and system organization
  • Deep knowledge of HPC and ML workloads, including scaling behavior and performance bottlenecks
  • Experience with scale-up and scale-out performance analysis at rack-level and cluster-level deployments
  • Strong analytical and problem-solving skills, with a high level of attention to detail
  • Excellent interpersonal, collaboration, and communication skills
  • Bachelor's or Master's degree in Computer Engineering, Electrical Engineering, Computer Science, or related field
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