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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 ...

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How much do nvidia research jobs pay per hour?

As of Jun 5, 2026, the average hourly pay for nvidia research in the United States is $39.39, according to ZipRecruiter salary data. Most workers in this role earn between $21.15 and $53.61 per hour, depending on experience, location, and employer.

What is an Nvidia Research job?

An Nvidia Research job involves conducting cutting-edge research in areas like artificial intelligence, computer graphics, and high-performance computing. Researchers work on innovative projects that push the boundaries of technology, often collaborating with academia and industry partners. These roles typically require expertise in machine learning, deep learning, hardware acceleration, or related fields. Team members publish papers, develop prototypes, and contribute to Nvidia's long-term technological advancements.

What are the key skills and qualifications needed to thrive in the Nvidia Research position, and why are they important?

Excelling in Nvidia Research typically requires a PhD or advanced degree in computer science, electrical engineering, or a related field, with strong expertise in machine learning, computer vision, and deep learning algorithms. Familiarity with programming languages such as Python and C++, and experience using frameworks like TensorFlow or PyTorch, as well as CUDA for GPU computing, are also important. Excellent problem-solving abilities, creativity, and effective collaboration and communication skills help set candidates apart. These skills are crucial for conducting innovative research, collaborating with multidisciplinary teams, and advancing the field of AI and graphics technology.

What opportunities for career growth and advancement are available within Nvidia Research?

Nvidia Research offers a dynamic environment where researchers can grow by taking on increasingly complex projects, publishing groundbreaking work, and collaborating with world-class experts. Many team members advance to senior and principal researcher roles or transition into leadership positions overseeing multi-disciplinary research initiatives. Nvidia also encourages continuous learning through conferences, workshops, and internal seminars, which further support professional development. As the company continues to expand its research footprint, there are ample opportunities to shape new areas of innovation and make a lasting impact on both the organization and the industry.

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Nvidia Research jobs near you
Infographic showing various Nvidia Research job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 88% Full Time, and 11% Part Time. Highlights an 84% Physical, 8% Hybrid, and 8% Remote job distribution, with an average salary of $81,931 per year, or $39.4 per hour.
AI and FSI Developer Technology Engineer- New College Grad 2026

AI and FSI Developer Technology Engineer- New College Grad 2026

Nvidia

New York, NY

Full-time

Posted 26 days ago

Job description

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.

Applications for this job will be accepted at least until April 13, 2026.

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.
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About Nvidia

Sourced by ZipRecruiter

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.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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