# Senior Validation Engineer

**Company**: NVIDIA
**Location**: Santa Clara, CA
**Experience**: senior
**Job type**: full-time
**Salary**: 136,000 USD - 212,750 USD for Level 3, and 168,000 USD - 258,750 USD for Level 4
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-Systems-Performance-Engineer_JR2029006?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_f819fece-437

## Description

NVIDIA is seeking a Senior Validation Engineer in the DGX Server Product Engineering Team. You will work with a team of HW/SW engineers to develop and implement complex automated test plans for GPU accelerated computing products.

**Responsibilities:**

- Develop and tune synthetic GPU workloads using CUDA or GPU programming DSLs, and application workload recipes using AI training and inference frameworks.

- 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.

- Analyze performance anomalies, workload correctness, and hardware and software failures.

- Build automation for workload deployment, experiment execution, telemetry collection, and analysis across systems and configurations.

**Requirements:**

- BS in Computer Engineering, Electrical Engineering, Computer Science, or a 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.

- Working knowledge of CUDA and GPU profiling tools.

- Experience debugging workloads and system behavior in Linux environments, and collaborating across hardware and software teams.

**Nice to Have:**

- Experience with NVIDIA Dynamo, TensorRT-LLM, vLLM, SGLang, or NCCL.

- CUDA kernel development or optimization experience using cuBLAS, CUTLASS, or related libraries.

- Familiarity with x86/Arm servers, NVLink, PCIe, InfiniBand/Ethernet, and distributed GPU systems.

- Experience using hardware error, power, thermal, and reliability telemetry to develop targeted stress coverage and isolate failures.

- A track record of building automation and turning experimental findings into measurable improvements in performance, coverage, or product quality.

NVIDIA offers highly competitive salaries and a comprehensive benefits package.

## Skills

### Required
- Computer Engineering
- Electrical Engineering
- Computer Science
- CUDA
- GPU programming
- Python
- data analysis
- AI training
- inference frameworks
- Linux

### Nice to have
- NVIDIA Dynamo
- TensorRT-LLM
- vLLM
- SGLang
- NCCL
- cuBLAS
- CUTLASS
- x86/Arm servers
- NVLink
- PCIe
- InfiniBand/Ethernet
- distributed GPU systems

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Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-Systems-Performance-Engineer_JR2029006?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)