Principal Software Engineer, E2E Performance and Goodput — CSP Engagements

NVIDIA Corporation; Austin (TX); On-site; USD 180,000 - 280,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation is seeking a Senior Systems Performance Engineer in Austin, TX, to lead end-to-end performance characterization and validation for CSP and hyperscale customers. The role focuses on ensuring workloads meet performance targets on NVIDIA platforms, analyzing cross-customer data, and driving optimization priorities across tools and configurations.

You will collaborate with engineering teams, communicate findings to technical and executive stakeholders, and influence product

Qualifications

• Requires 15+ years of systems performance engineering experience in GPU/HPC/ML infrastructure.
• Bachelor's or Master's degree in a related field or equivalent experience.
• Candidates should have GPU profiling and distributed training expertise and strong data analysis skills.

Responsibilities

• Lead end-to-end performance characterization and validation with CSP and hyperscale customers to ensure workloads meet targets.
• Analyze cross-customer performance patterns and translate feedback into optimization priorities across tools, configurations, and NVIDIA software/hardware systems.
• Coordinate improvements with engineering teams and communicate with technical and executive audiences.

Skills

Systems Performance Engineering

GPU Workload Profiling

Distributed Training Performance

Performance Characterization

Performance Analysis

Statistical Analysis

Python

Pandas

Performance Regression Detection

GPU Architecture

Memory Bandwidth Optimization

Customer Engagement

Cross-Functional Leadership

Benchmarking

Education

Bachelor's or Master's in a related field

Tools

CUDA

NCCL

Job description

Lead end-to-end performance characterization and validation with CSP and hyperscale customers, ensuring workloads meet performance targets on NVIDIA platforms. Analyze cross-customer performance patterns, incorporate customer feedback into optimization priorities, and coordinate improvements to tools, configurations, and NVIDIA software and hardware systems.

Requirements:

Requires 15 or more years of systems performance engineering experience, ideally in GPU, HPC, or ML infrastructure, and a bachelor's or master's degree in a related field or equivalent experience. Candidates should have GPU profiling and distributed training expertise, strong statistical and data analysis skills, knowledge of the software stack's performance effects, and the ability to influence engineering teams and communicate with technical and executive audiences.

Key Skills:

Systems Performance Engineering, GPU Workload Profiling, Distributed Training Performance, Performance Characterization, Performance Analysis, Statistical Analysis, Python, Pandas, Performance Regression Detection, CUDA, NCCL, GPU Architecture, Memory Bandwidth Optimization, Customer Engagement, Cross-Functional Leadership, Benchmarking

Benefits:

Equity, Benefits