Senior GPU Systems Performance Engineer

NVIDIA Corporation; Austin (TX); On-site; USD 136,000 - 259,000; Full time

Job summary

NVIDIA is seeking a Senior Validation Engineer for the DGX Server Product Engineering Team in Austin. You will design, implement, and automate validation for GPU-accelerated systems, profiling workloads, and coordinating with HW/SW teams to drive fixes.

Strong CUDA, Python, and Linux skills are essential. You will develop and stress-test AI training and inference workloads across GPU platforms, build performance models, and analyze telemetry to ensure robust system behavior.

Qualifications

• BS in Computer Engineering, Electrical Engineering, Computer Science, or related field, or equivalent experience.
• 5+ years of relevant experience in systems performance engineering, performance modeling, accelerated computing, or complex system development and debug.
• Deep understanding of computer architecture, including GPU and CPU execution, memory hierarchies, interconnects, and their impact on application performance.
• Experience developing analytical or simulation-based performance models and validating predictions against measurements from running systems.
• Hands‑on experience deploying, profiling, and tuning AI training or inference workloads using frameworks such as PyTorch, TensorRT‑LLM, vLLM, or SGLang.
• Strong Python programming and data analysis skills, including designing controlled experiments, interpreting telemetry, and communicating findings.
• Working knowledge of CUDA and GPU profiling tools, with the ability to connect application behavior to hardware utilization and bottlenecks.
• Experience debugging workloads and system behavior in Linux environments, and collaborating across hardware and software teams.

Responsibilities

• Develop and tune synthetic GPU workloads using CUDA or GPU programming DSLs, and application workload recipes using AI training and inference frameworks, to stress targeted hardware subsystems and expand validation coverage.
• Onboard and adapt state-of-the-art AI training and inference workloads to new GPU platforms.
• Apply architectural analysis and develop system‑level performance models to characterize workload behavior, identify bottlenecks, and guide workload selection and stress coverage.
• Design controlled experiments and correlate model predictions with workload profiles, system telemetry, and measured results; investigate differences and refine workloads, models, and test strategies.
• Analyze performance anomalies, workload correctness, and hardware and software failures; create reproducible cases and partner with architecture, design, and software teams to drive fixes and verify improvements.
• Build automation for workload deployment, experiment execution, telemetry collection, and analysis across systems and configurations.

Skills

CUDA

Python

Linux

GPU profiling

Performance modeling

AI workloads (PyTorch/TensorRT-LLM)

Telemetry analysis

System debugging

Education

BS in Computer Engineering/Electrical Engineering/CS

Tools

CUDA toolchain

GPU tracing tools

TensorRT-LLM

vLLM

SGLang

Job description

NVIDIA is seeking a Senior Validation Engineer for the DGX Server Product Engineering Team in Austin. You will design, implement, and automate validation for GPU-accelerated systems, profiling workloads, and coordinating with HW/SW teams to drive fixes.

Strong CUDA, Python, and Linux skills are essential. You will develop and stress-test AI training and inference workloads across GPU platforms, build performance models, and analyze telemetry to ensure robust system behavior.