Senior Performance Engineer for Scalable AI Workloads

NVIDIA; Oregon (WI); On-site; USD 224,000 - 431,250; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA's DGX Cloud AI Efficiency Team seeks a Senior Performance Engineer to characterize workloads, establish performance baselines, diagnose bottlenecks, and drive optimizations from investigation through deployment. You will partner with deep learning engineers, platform teams, and GPU architects to deliver measurable improvements in large-scale AI systems.

Your work turns complex measurements into prioritized engineering decisions, shaping scalable DGX Cloud deployments and advancing

Qualifications

• BS or higher in computer science or computer engineering or a related field.
• 12+ years of experience with strong C++ and Python programming.
• Solid foundation in OS, architecture, and distributed systems.
• Experience with performance engineering, benchmarking, profiling, and optimization.
• Ability to communicate findings and align across teams.

Responsibilities

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

Skills

C++

Python

Performance engineering

Benchmarking

Profiling

Distributed systems

Operating systems

Communication

Education

Bachelor's degree in computer science or computer engineering

Job description

NVIDIA's DGX Cloud AI Efficiency Team seeks a Senior Performance Engineer to characterize workloads, establish performance baselines, diagnose bottlenecks, and drive optimizations from investigation through deployment. You will partner with deep learning engineers, platform teams, and GPU architects to deliver measurable improvements in large-scale AI systems.

Your work turns complex measurements into prioritized engineering decisions, shaping scalable DGX Cloud deployments and advancing