Performance Engineering Intern, Deep Learning and HPC - 2027

Overview

• We are now looking for a Performance Engineer Intern to support our growing investments in performance testing of various NVIDIA‘s datacenter products and applications.
• Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing.
• An era in which our GPUs, CPUs, interconnects and software together act as the brains of the AI factories that power it.
• You will be part of the global Performance Lab team, improving our capacity to expertly and accurately benchmark state-of-the-art AI applications and products.
• We also work to develop infrastructures and solutions that enhance the team’s ability to gather data through automation and designing efficient processes for testing a wide variety of applications and hardware.
• The data that we collect drives marketing/sales collaterals as well as engineering studies for future products.
• 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.
• What you’ll be doing: Benchmark, profile, and analyze AI and HPC workloads on NVIDIA supercomputers and distributed systems - LLM and VLM training and inference, agentic workloads, world models, and Physical AI for robotics.
• Aggregate and produce written reports with the testing data for internal sales, marketing, SW, and HW teams.
• Build benchmark automation with AI agents and agentic coding tools.
• Ensure the whole process and results are reliable and reproducible.
• Collaborate with internal teams to debug and resolve performance issues.
• Set up and configure systems with appropriate hardware and software to run benchmarks.
• What we need to see: Currently pursuing a bachelor's degree (or higher) in Computer Science, Electrical Engineering, or a related field.
• Experienced in programming and debugging with scripting languages such as Python or Unix shell.
• Hands-on experience with Linux based systems.
• Familiarity using a container platform such as Docker.
• Fluent with AI coding assistants and agentic workflows, with the judgment to verify what they produce rather than defer to them.
• Hands-on experience with inference frameworks such as TensorRT-LLM, vLLM, or SGLang.
• Or experience in AI model inference deployment and training.
• Strong data analysis skills and the ability to summarize findings in a written report.
• Strong English verbal and written skills to improve collaboration with coworkers.
• Ways to stand out from the crowd: Experience with CI/CD pipelines and modern DevOps practices.
• Familiar with cloud provisioning and scheduling tools (Kubernetes, Slurm).
• Experience building agent workflows, MCP tools, or reusable agent skills that other people use.
• Curiosity about GPUs, TPUs, cloud and performance benchmarking.
• Background in system-level problem solving.
• 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 & Gaming, we would love for you to join us.