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. NVIDIA's invention of the GPU 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU computing ignited the era of AI. NVIDIA is constantly evolving by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world.
We are looking for you to join NVIDIA’s Performance Lab where you will be encouraged to craft and build outstanding software solutions that challenge NVIDIA products in new ways. Our team values passion, and positive interactions with teammates. We offer the opportunity to work on cutting edge technologies in the fields of AI, Graphics Rendering, and Datacenters.
What you'll be doing:
Writing and maintaining containerized GPU accelerated workloads for the financial services industry, from deep learning training and inference, to portfolio optimization and backtesting.
Running, validating, and analyzing benchmarking models at scale on HPC clusters.
Visualizing performance data, building charts and dashboards using internal schemas and tooling.
Working closely with the latest and greatest in financial AI models and tooling to help build reference models for NVIDIA.
What we need to see:
Bachelors degree in Computer Engineering, Software Engineering, Computer Science, or related field (or equivalent experience) with 8+ years of experience.
Desire to improve code quality by learning and applying computer science fundamentals, algorithms, and data structures.
Comfort with teamwork, collaboration, and a desire to reach across functional borders to develop new partnerships.
Professional experience with Python.
Working comfort in a Linux command-line environment with version control.
Foundational understanding and interest of the machine learning lifecycle (training, evaluation, and inference).
Ways to stand out from the crowd:
Familiarity with PyTorch and/or training, testing, and evaluating machine learning models.
Experience with GPU computing or CUDA and libraries like cuOPT, CUTLASS, cuDNN, etc.
Exposure to workload orchestration and job schedulers (Kubernetes, Slurm).
Experience with containerized applications and resource management.
Interest in quantitative finance and applying performance data to real-world problems.
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/
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, Software Engineering, Computer Science, or related field (or equivalent experience) with 8+ years of experience
- Professional experience with Python
- Working comfort in a Linux command-line environment with version control
- Desire to improve code quality by learning and applying computer science fundamentals, algorithms, and data structures
- Comfort with teamwork, collaboration, and cross-functional partnership
- Foundational understanding and interest in the machine learning lifecycle (training, evaluation, inference)
- Familiarity with PyTorch and training/testing/evaluating ML models
- Experience with GPU computing or CUDA and libraries like cuOPT, CUTLASS, cuDNN
- Exposure to workload orchestration and job schedulers (Kubernetes, Slurm)
- Experience with containerized applications and resource management (containers, Docker)
- Interest in quantitative finance and applying performance data to real-world problems
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.”
