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.
We are looking for a HPC Performance Engineer in our NVHPC compilers & tools group. Our performance engineers analyze High Performance Computing (HPC) applications with the intent of improving performance by driving compiler optimizations and library enhancements. This role offers the chance to work with a wide range of applications, from small benchmarks running on single-CPU core to full-scale applications running on multi-node multi-GPU systems. You'll find optimization opportunities and work closely with our compiler development and application engineering teams to deliver effective solutions.
What you'll be doing:
Analyze the effect of different compilers and compiler optimizations on HPC application performance.
Evaluate whether and how the compiler and runtime can improve the performance of key HPC applications on CPU and CPU/GPU platforms.
Communicate limits of compiler capabilities with application engineering to guide the best path forward towards improving performance.
Port HPC applications to different platforms and programming models.
Evaluate the impact of NVHPC package components, device driver, and system configuration on application performance.
What we need to see:
BS/MS or equivalent experience in Computer Science or a related engineering field.
5+ years of programming experience.
Solid understanding of Fortran, C, C++, and programming techniques, especially for parallel architectures, preferably for compilers.
Experience with OpenACC, OpenMP, MPI, CUDA and Standard Language Parallelism.
Strong skills in performance analysis and tuning, as well as a broad understanding of parallel applications development tools and runtime environments.
Strong mathematical fundamentals, including linear algebra and numerical methods.
Understand performance considerations, tradeoffs, and impact.
Expert interpersonal skills, a logical approach to problem-solving, good time management, and task prioritization skills. Excellent written and verbal communication skills, along with the ability to work in a dynamic development team.
Ways to stand out from the crowd:
You have a deep understanding of machine architectures and micro-architectures.
Experience with debugging and porting as well as assembly language programming is a significant advantage.
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 152,000 USD - 241,500 USD.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
- BS/MS or equivalent experience in Computer Science or a related engineering field.
- 5+ years of programming experience.
- Solid understanding of Fortran, C, and C++ and programming techniques for parallel architectures (preferably compilers).
- Experience with OpenACC, OpenMP, MPI, CUDA and Standard Language Parallelism.
- Strong skills in performance analysis and tuning, and understanding of parallel applications development tools and runtime environments.
- Strong mathematical fundamentals, including linear algebra and numerical methods.
- Understanding of performance considerations, tradeoffs, and impact.
- Expert interpersonal, problem-solving, time management, and written/verbal communication skills; ability to work in dynamic teams.
- Deep understanding of machine architectures and micro-architectures.
- Experience with debugging, porting, and assembly language programming.
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.”
