Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team!
We’re looking for an AI Developer Technology Engineer to push the limits of performance at the intersection of AI, high-performance computing, and financial markets. In this role, you’ll dive deep into parallel algorithms, GPUs, and complex systems to identify and eliminate bottlenecks, unlocking the full power of the world’s most advanced processing hardware. You’ll collaborate with top experts across industry and academia, influence next-generation platforms, and share your insights with the global developer community. Would you enjoy solving hard technical problems, love performance tuning, and want your work to have a visible impact across an entire industry? If so, we would love to invite you to consider this role!
What you will be doing:
Researching, designing, and developing groundbreaking techniques to accelerate high-performance workloads for FSI-focused, pioneering AI on NVIDIA CPUs and GPUs.
Working with leading technical experts to analyze, optimize, and scale complex AI and HPC workloads for modern CPU and GPU architectures.
Profiling and eliminating performance bottlenecks across the stack: from algorithms to kernels to system-level behavior.
Publishing and presenting your work in conferences, talks, and blogs to educate and inspire the broader developer community.
Influencing the design of future hardware architectures, system software, libraries, and programming models by collaborating closely with NVIDIA research, hardware, compiler, and tools teams.
What we need to see:
Pursuing or recently completed a Master’s or PhD degree (or equivalent experience) in Computer Science, Computer Engineering, or Electrical and Computer Engineering or related field.
Relevant work or research experience.
Experience with low-level parallel programming (e.g., CUDA).
Deep understanding of CPU/GPU architecture fundamentals and how they impact performance.
Fluency in C/C++ and solid foundations in algorithms and software design.
Experience improving the performance of large-scale computational applications on GPUs.
Good understanding of linear algebra.
Strong communication and organization skills, with a logical approach to problem solving and solid prioritization abilities.
Ways to stand out from the crowd:
Prior internship experience in a related field.
Experience with inference optimization techniques and deploying optimized AI models in production.
Experience with TensorRT, TensorRT-LLM, and cuTile.
Background in capital markets with exposure to systematic/algorithmic strategies or quantitative trading.
Experience parallelizing and optimizing machine learning methods such as decision trees, time series models, and Monte Carlo simulations as well as knowledge of financial data models, pricing and risk simulation algorithms, portfolio optimization, or other finance-focused applications and services.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 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 a diverse 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
- Pursuing or recently completed Master's or PhD in Computer Science or related field
- Experience with low-level parallel programming (e.g., CUDA)
- Fluency in C/C++ and solid foundations in algorithms and software design
- Deep understanding of CPU/GPU architecture fundamentals
- Experience improving performance of large-scale computational applications on GPUs
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.”
