Performance Engineer Intern, Deep Learning and HPC

1 Month ago • Upto 1 Years • Research & Development

Job Summary

Job Description

This internship involves benchmarking, profiling, and analyzing the performance of AI workloads (LLM training and inference) and HPC on NVIDIA supercomputers and distributed systems. The intern will generate reports, set up systems, debug performance issues, develop Python automation scripts, and assist in developing automated testing tools and processes. Collaboration with internal teams across sales, marketing, software, and hardware is key. The role requires strong data analysis, Linux experience, and familiarity with container platforms like Docker or Singularity. The intern will contribute to improving the efficiency and quality of NVIDIA's data center computing products and applications.
Must have:
  • Python/Unix scripting
  • Data analysis & reporting
  • Linux system experience
  • Container platform familiarity (Docker/Singularity)
  • Software compilation & execution
Good to have:
  • GPU/CPU benchmarking
  • ML/DL techniques (TensorFlow/PyTorch)
  • AI model development & deployment
  • Cloud provisioning (Kubernetes, SLURM)
  • Testing automation

Job Details

We are now looking for a Performance Engineer Intern to support our growing investments in perf testing of various company 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 GPU acts as the brains of computers, robots, and self-driving cars that can understand the world, all while striving to deliver the highest possible performance of our products.

You will be part of global Performance Lab team, improving our capacity to expertly and accurately benchmark state-of-the-art datacenter applications and products. We also work to develop new scripts 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 current and 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 the performance of AI workloads specifically tailored for large-scale LLM training and inference, as well as High-Performance Computing (HPC) on NVIDIA supercomputers and distributed systems.

  • Aggregate and produce written and visual reports with the testing data for internal sales, marketing, SW, and HW teams

  • Setup and configure systems with appropriate hardware and software to run benchmarks

  • Collaborate with internal teams to debug and improve performance issues

  • Develop Python scripts to automate the testing of various applications

  • Assist with the development of tools and processes that improve our ability to perform automated testing

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.

  • Strong data analysis skills and the ability to summarize findings in a written report

  • Hands-on experience with Linux based systems. Familiarity using a container platform such as Docker or Singularity. Experience with compiling and running software from source code.

  • Fast and self-learning capabilities with strong analytical and problem-solving skills.

  • Good English verbal and written interpersonal skills to improve collaboration with coworkers

Ways to stand out from the crowd:

  • Background with GPU/CPU benchmarking

  • Familiar with ML/DL techniques, algorithms and frameworks like TensorFlow or PyTorch.

  • Experience in AI model development, training, evaluation and deployment on Cloud, Cluster or on-premises. Familiar with cloud provisioning and scheduling tools (Kubernetes, SLURM).

  • Exposure to testing automation for various applications.

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.

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About The Company

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.


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