NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re 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. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
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. We are now looking for a Performance Engineer focused on Deep Learning (DL) & High-Performance Computing (HPC) applications to join our diverse team.
What you'll be doing:
- Plan and execute 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 areas of advanced machine learning and HPC.
- Assist with the development of tools and processes that improve our ability to perform automated testing.
What we need to see:
- B.S. in Computer Engineering, Computer Science or related technical field (or equivalent experience).
- 2+ years of experience.
- 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 PyTorch, MXNet, or TensorRT.
- Experience using GPU-enabled HPC applications such as LAMPS, GROMACS, Amber, RTM, etc…
- GPU/CPU benchmarking on cloud solutions from AWS, GCP, Azure.
- Software compilers such as GNU, Intel Composer, or PGI.
- Previous experience with computer clusters and cluster orchestration and scheduling tools.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 116,000 USD - 189,750 USD for Level 2, and 136,000 USD - 212,750 USD for Level 3.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.Skills Required
- Bachelor's degree in Computer Engineering, Computer Science, or a related technical field, or equivalent experience
- 2+ years of experience
- Excellent programming and debugging skills in Python or Unix shell
- Advanced knowledge of Linux-based systems, especially Ubuntu and CentOS
- Proficiency compiling software from source code and debugging compilation errors
- Excellent English verbal and written interpersonal skills
- Excellent data analysis skills and ability to summarize findings in written reports
- Familiarity with Docker or Singularity
- Experience with GPU-enabled deep learning frameworks such as PyTorch, MXNet, or TensorRT
- Experience with GPU-enabled HPC applications such as LAMMPS, GROMACS, Amber, or RTM
- GPU or CPU benchmarking on AWS, GCP, or Azure
- Experience with GNU, Intel Composer, or PGI compilers
- Experience with computer clusters and cluster orchestration or scheduling tools
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
