# Performance Engineer Intern, Systems Software- Fall 2026

**Company**: NVIDIA
**Location**: St. Louis, MO
**Job type**: internship
**Salary**: $20-$71 per hour
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-MO-St-Louis/Performance-Engineer-Intern--Systems-Software---Fall-2026_JR2015779?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_5c28425c-965

## Description

You will join the team responsible for maintaining, developing, and executing Desktop Gaming Performance testing in Linux and Windows environments for the world's fastest, power-efficient GPUs. This internship has a preferred duration of 8-12 months and offers an hourly rate of $20-$71.

**Responsibilities:**

- Write and maintain containerized GPU-accelerated workloads for the financial services industry, including deep learning training and inference, portfolio optimization, and backtesting.

- Run, validate, and analyze benchmarking models at scale on HPC clusters.

- Visualize performance data, build charts, and create dashboards using internal schemas and tooling.

- Collaborate with the latest financial AI models and tooling to build reference models for NVIDIA.

**Requirements:**

- Currently enrolled in a Bachelor's program majoring in Computer Engineering, Software Engineering, Computer Science, or a related field.

- Desire to improve code quality by applying computer science fundamentals, algorithms, and data structures.

- Comfortable with teamwork, collaboration, and developing new partnerships.

- Active experience with Python.

- Working knowledge of Linux command-line environments with version control.

- Foundational understanding of the machine learning lifecycle (training, evaluation, and inference).

**Preferred Qualifications:**

- Familiarity with PyTorch and/or training, testing, and evaluating machine learning models.

- Experience with GPU computing or CUDA and libraries like cuOPT, CUTLASS, cuDNN, etc.

- Exposure to workload orchestration and job schedulers (Kubernetes, Slurm).

- Experience with containerized applications and resource management.

- Interest in quantitative finance and applying performance data to real-world problems.

**Benefits:**

- Eligible for intern benefits

## Skills

### Required
- Python
- Linux
- version control
- computer science fundamentals
- algorithms
- data structures
- machine learning lifecycle

### Nice to have
- PyTorch
- GPU computing
- CUDA
- cuOPT
- CUTLASS
- cuDNN
- Kubernetes
- Slurm
- containerized applications
- resource management
- quantitative finance

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Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-MO-St-Louis/Performance-Engineer-Intern--Systems-Software---Fall-2026_JR2015779?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)