Senior Performance Engineer — Large-Scale AI Optimization

NVIDIA AI

Eugene (OR)

On-site

USD 224,000 - 431,250

Full time

14 days+

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Benefits

Job summary

NVIDIA DGX Cloud AI Efficiency Team is seeking a Senior Performance Engineer to characterize workloads, establish baselines, diagnose bottlenecks, and drive optimizations from investigation through deployment. You will influence system and software design by turning measurements into actionable insights and partnering with GPU architects and engineers.

Join a technically diverse team dedicated to advancing performance, efficiency, and resiliency of large-scale AI workloads.

Qualifications

12+ years of experience with C++ and Python in performance-focused roles.
Strong foundation in operating systems, computer architecture, and distributed systems.
Experience with performance engineering, benchmarking, profiling, and optimization of complex software or systems.
Ability to communicate technical findings and align across teams.
Experience analyzing end-to-end performance of large-scale AI workloads across compute, network, storage, and software stacks.

Responsibilities

Analyze end-to-end performance of large-scale AI workloads across compute, network, storage, and software stacks.
Design and execute rigorous performance studies to establish baselines, diagnose regressions, and quantify bottlenecks.
Define performance and efficiency evaluation methodologies, benchmarks, and success metrics for AI workloads.
Use profiling, observability, and data analysis to turn performance measurements into actionable optimization plans.
Partner with deep learning engineers, platform teams, and GPU architects to validate and deliver performance improvements.
Communicate performance findings, tradeoffs, and recommendations clearly to influence system and software design decisions.