Jobs · Engineering · California

Sr. Manager, Technical Product Management

AMD · Santa Clara, CA · 1 wk ago
HybridEngineeringFull-time

About the role

The Team AMD's Data Center GPU organization is transforming the industry with their AI-based Graphics Processors. Their primary objective is to design exceptional products that drive the evolution of computing, serving as the foundation for enterprise data centers, artificial intelligence (AI), HPC, and embedded systems.

Responsibilities

  • Develop and maintain models to evaluate system and workload performance across diverse use cases.

  • Generate forward-looking performance projections to guide product strategy, identify bottlenecks, and inform architectural and product tradeoffs.

  • Develop total cost of ownership (TCO) frameworks that incorporate hardware, software, efficiency, utilization, and infrastructure considerations.

  • Perform competitive benchmarking and analysis to position AMD solutions effectively in terms of performance-per-dollar and performance-per-watt.

  • Engage directly with leading Hyperscalers, CSPs, OEMs, and ODMs to understand workload characteristics, performance needs, and economic drivers.

  • Collaborate to ensure alignment between customer requirements and AMD’s product direction.

  • Synthesize performance insights, customer feedback, and industry trends into clear, compelling narratives that influence cross-functional teams, including architecture, engineering, and product management.

  • Participate in industry forums, benchmarking efforts, and technical conferences to stay current on workload trends, performance methodologies, and competitive positioning.

Required Qualifications

  • MS in Computer Science, Computer Engineering, Electrical Engineering, or related field (PhD preferred)

  • 5+ years in performance analysis, system architecture, or technical product management in datacenter, AI/ML, or HPC domains

  • Strong experience with system-level performance analysis (compute, memory, networking, storage)

  • Proficiency in performance modeling, benchmarking, and workload characterization

  • Experience with AI/ML and/or HPC workloads and large-scale distributed systems

  • Demonstrated ability to build and apply TCO models (performance-per-dollar, performance-per-watt)

  • Solid programming skills (e.g., Python, C++) for modeling and analysis

  • Prominent ability to influence product or architecture decisions through data-driven insights

  • Strong cross-functional communication skills, including customer-facing engagement

Key Success Factors & Competencies

  • System-Level Thinking: Identifies root causes and trade-offs across hardware, software, and infrastructure

  • Performance & Cost Insight: Connects architectural decisions to real-world performance and TCO outcomes

  • Influence: Drives alignment across engineering, architecture, and product teams without direct authority

  • Customer Focus: Translates workload and hyperscaler needs into actionable product guidance

  • Clarity of Communication: Synthesizes complex analysis into clear, decision-oriented narratives

  • Ownership: Operates independently, driving ambiguous problems to concrete recommendations

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