Performance Engineering Intern, Deep Learning and HPC - Winter 2026

NVIDIA builds the most advanced data center GPUs in world that are utilized in a growing number of computing areas ranging from life sciences to deep learning to quantum chemistry. NVIDIA strives to deliver the best possible performance, which allows researchers and scientists to do more world-changing work than ever before. We are now looking for a Performance Engineer Intern focused on Deep Learning (DL) & High-Performance Computing (HPC) applications to join our diverse team.

Our team is responsible for generating benchmark data across a rapidly growing catalog of Deep Learning & HPC frameworks/applications on Nvidia and as well as competitive products. The data that we collect drives marketing/sales collaterals as well as engineering studies for current and future products. In some instances, we’ll write scripts that improve the team’s ability to gather data through automation and designing efficient processes for testing a wide variety of applications and hardware. You will have the opportunity to work with multi-functional teams and in a dynamic environment where multiple projects will be active at once and priorities may shift frequently.

Preferred duration of the internship: 8 months minimum

What you’ll be doing:

• Plan and execute GPU performance benchmarking across a wide range of HPC and DL frameworks and applications
• Aggregate, analyze, and generate written and visual reports with the testing data for internal sales, marketing, SW, and HW teams
• Develop Python scripts to automate the testing of DL & HPC-focused applications
• Work with internal engineering team to debug performance issues
• Learn to use the latest applications in the fields of Deep Learning and HPC
• Assist with the development of tools and processes that improve our ability to perform automated testing

What we need to see:

• Pursuing bachelors degree in Computer Engineering, Computer Science or related technical field
• Excellent programming and debugging skills in a scripting language such as Python or Unix shell
• Advanced knowledge using Linux based systems (Ubuntu and CentOS strongly preferred)
• Proficient in compiling software from source code, including debugging errors encountered
• Excellent English verbal and written interpersonal skills to improve collaboration with coworkers
• Excellent data analysis skills and the ability to summarize findings in a written report
• Familiarity using a container platform such as Docker or Singularity

Ways to stand out from the crowd:

• Experience using a GPU-enabled deep learning framework such as TensorFlow, PyTorch, MXNet, or TensorRT
• Experience using GPU-enabled HPC applications such as LAMMPS, GROMACS, Amber, RTM, etc…
• Experience with GPU/CPU benchmarking on cloud solutions from AWS, GCP, Azure
• GPU programming experience in CUDA, OpenACC, or OpenCL
• Familiarity with software compilers such as GNU, Intel Composer, or PGI
• Previous experience with computer clusters, Slurm, Kubernetes.

We have some of the most forward thinking and hardworking people in the world working for us and our best-in-class engineering teams are rapidly growing. We are building a team that will help shape the future of data center computing. If you are passionate about new technologies, care about improving efficiency and quality, and want to be at the forefront of AI & HPC, we would love for you to join us.

Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 20 USD - 71 USD.


You will also be eligible for Intern benefits. ​

Applications for this job will be accepted at least until December 14, 2025.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.