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Senior System GPU Performance Engineer

NVIDIA· Engineer, ASIC
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Shanghai, Chinafull-timePosted 3w ago

About the role

Senior System GPU Performance Engineer to maximize performance and power efficiency of production GPU systems; owns analysis from hypothesis to product impact and collaborates across multiple teams to translate workload behavior into platform improvements.

Responsibilities

  • Own system-level GPU performance and power characterization from first silicon through production across representative applications, benchmarks, and product configurations.
  • Drive performance and power feature productization, translating measured behavior into firmware, driver, BIOS, platform, and silicon recommendations that meet product targets and speed-of-light schedules.
  • Design experiments, execute test plans, and build models that isolate bottlenecks across GPU compute, memory, interconnect, CPU interaction, power delivery, and thermal limits.
  • Analyze production-silicon data across process, voltage, temperature, workloads, and bins to quantify performance-per-watt trade-offs and identify causal optimization opportunities.
  • Lead multi-functional root-cause closure across architecture, design, validation, software/firmware, power and thermal, reliability, ATE, product management, manufacturing, and operations; own fixes through confirmation.
  • Establish reusable automation, visualization, and closed-loop methodologies that improve experiment coverage, analysis accuracy, debug velocity, and learning across future GPU programs.
  • Translate complex system signals into decision-ready options for executive leadership on feature readiness, product configuration, targets, and program risks.

Qualifications

  • BS or MS in Electrical Engineering, Computer Engineering, Computer Science, Systems Engineering, or related field (or equivalent experience).
  • 8+ overall years of experience in GPU or system performance engineering, post-silicon characterization, silicon productization, or hardware-software performance optimization.
  • Hands-on experience with silicon bring-up, frequency and power characterization, product binning, and performance-per-watt optimization across process, voltage, temperature, workloads, and system configurations.
  • Strong understanding of GPU and system architecture, including compute pipelines, memory hierarchy, interconnects, CPU-GPU interactions, scheduling, telemetry, and sustained-performance limits.
  • Proven ability to design controlled experiments, develop performance or power models, analyze large datasets, and use statistics to separate bottlenecks and causal effects from noise.
  • Strong programming and analysis skills using Python and one or more of C, C++, SQL, JMP, or equivalent, with experience automating tests, data processing, and visualization.
  • Demonstrated ability to structure ambiguous system-level problems and drive them to root-cause closure across globally distributed, multi-functional hardware and software teams.
  • Strong written and verbal communication; able to translate complex technical issues into crisp, decision-ready options for executive leadership.

Skills

Required:System-level performance analysisExperiment design and data modelingProgramming and automationCross-functional leadershipCommunication

Benefits

  • Competitive benefits
  • Continuous learning
  • Team environment where everyone can do their best work.
Last updated Oct 2, 2026. Interested? Apply on the company site.

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