Nvidia
Nvidia

60 Nvidia Research Software Engineer Jobs Hiring Near You

Senior Software Engineer - NVIDIA Warp

Seattle, WA · On-site

$139K - $183K/yr

... software engineering skills in C++ and Python, comfortable working across build systems and ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive ...

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Nvidia Jobs Information

What is it like to work at Nvidia?

Nvidia is known for its collaborative and innovative culture, prioritizing teamwork and creativity to drive technological advancements. The company's structure is organized into various teams, including research and development, engineering, and sales, with a focus on fostering open communication and knowledge sharing across departments. Working at Nvidia may appeal to candidates who are passionate about artificial intelligence, graphics, and high-performance computing, as the company offers opportunities to contribute to cutting-edge projects and collaborate with experts in the field.

What makes Nvidia an attractive place to work?

Nvidia is a leading technology company in the field of artificial intelligence, graphics processing units, and high-performance computing, with a strong reputation for innovation and industry leadership. The company's workplace culture values collaboration, creativity, and innovation, with opportunities for employees to work on cutting-edge projects and contribute to the development of groundbreaking technologies. Joining Nvidia offers professionals a chance to be part of a dynamic and forward-thinking organization, with opportunities for growth, professional development, and making a meaningful impact in the tech industry.

How easy is it to get time off at Nvidia?

Most people find it easy to get time off.
100% of people report it’s easy to get time off.
Based on data from 5 people who took the Breakroom Quiz between December 2024 and December 2025.

How easy is it to take sick days at Nvidia?

Most people find it easy to take sick days.
100% of people report that it’s easy to take time off if they are sick.
Based on data from 5 people who took the Breakroom Quiz between December 2024 and December 2025.

Do people at Nvidia get to take their breaks without interruption?

Most people get breaks without interruption.
100% of people report that they get to take their breaks without interruption.
Based on data from 5 people who took the Breakroom Quiz between December 2024 and December 2025.

Is it stressful to work at Nvidia?

Some people feel stressed out here.
40% of people say they often feel stressed out at work.
Based on data from 5 people who took the Breakroom Quiz between December 2024 and December 2025.

Do people at Nvidia recommend working with their team?

Only some people recommend working with their team.
40% of people report that they wouldn’t recommend working with their immediate team to a friend.
Based on data from 5 people who took the Breakroom Quiz between December 2024 and December 2025.

Do people get enough training when they start at Nvidia?

Some people didn’t get enough training when they started.
40% of people report they didn’t get enough training when they started working here.
Based on data from 5 people who took the Breakroom Quiz between December 2024 and December 2025.

Do people get support to advance at Nvidia?

Most people are given support to advance their career here.
In the last year, 100% of people report being given support to advance their career here.
Based on data from 5 people who took the Breakroom Quiz between December 2024 and December 2025.

Do workers feel well informed about how Nvidia is doing?

Most people feel well informed about how the company is doing.
80% of people feel that they are kept well informed about how the company is doing as a whole.
Based on data from 5 people who took the Breakroom Quiz between December 2024 and December 2025.
Infographic showing various Research Software Engineer job openings at Nvidia in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 86% Physical, 12% Hybrid, and 2% Remote job distribution.
Senior AI and Quant DevTech Engineer

Senior AI and Quant DevTech Engineer

Nvidia

Santa Clara, CA • Hybrid

Full-time

Posted 5 days ago


Nvidia rating

9.3

Company rating: 9.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

15th of 209 rated software companies


Job description

We are looking for a software engineer with a strong background in parallel processing and GPU architecture to push the limits of performance at the intersection of AI, high-performance computing, and financial markets. In this role, you will dive deep into parallel algorithms, GPUs, and sophisticated systems, identifying and eliminating bottlenecks to unlock the full power of the world's most advanced processing hardware.

You will collaborate with top experts across industry and academia, influence next-generation platforms, and share your insights with the global developer community. Do 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'd love for you to consider this role.

What you will be doing:

  • Designing and developing groundbreaking techniques to accelerate high-performance workloads at the intersection of AI, math, and financial systems.

  • Working hands-on 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:

  • Strong hands-on experience with CUDA and parallel programming.

  • Deep understanding of CPU/GPU architecture fundamentals and how they impact performance.

  • A Master's or PhD in Computer Science, Computer Engineering, Electrical and Computer Engineering, or a related field.

  • Fluency in C/C++ and a solid foundation in algorithms and software design.

  • 5+ years of relevant work or research experience.

  • Proven experience improving the performance of large-scale computational applications on GPUs.

  • Excellent understanding of linear algebra.

  • Strong communication and organizational skills, with a logical approach to problem-solving and solid prioritization abilities.

Ways to stand out from the crowd:

  • Experience with inference optimization techniques and deploying optimized AI models in production.

  • Experience with TensorRT, TensorRT-LLM, and cuTile.

  • Experience parallelizing and optimizing machine learning methods such as decision trees, time-series models, and Monte Carlo simulations.

#LI-Hybrid

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 for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 14, 2026.

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.

What Nvidia employees say

Hours and flexibility

Workplace

Get the full story on Breakroom


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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