Developer Technology Engineer, Public Sector

About NVIDIA

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!

NVIDIA is hiring passionate, world-class computer scientists and engineers to work in its Public Sector Developer Technology (Devtech) team! In this Developer Technology Engineer, Public Sector role, you will research and develop techniques to GPU-accelerate leading applications in fields targeting applications in the federal ecosystem. You will be performing in-depth analysis and optimization to ensure the best possible performance on current and next-generation GPU architectures.

What You Will Be Doing

• Working directly with key application developers to understand the current and future problems they are solving, crafting and optimizing core parallel algorithms and data structures to provide the best solutions using GPUs, through reference code development, direct contribution to the full software stack including libraries, applications, and high productivity software environments (e.g. Python).
• Collaborating closely with diverse groups at NVIDIA such as the architecture, research, libraries, tools, and system software teams to influence the design of architectures, software, and programming models, by investigating the impact on application performance and developer productivity.
• Occasional travel from time to time for conferences and on-site visits with developers.

What We Need To See

• Pursuing or recently completed a BS, MS, or PhD degree or equivalent experience in an engineering or computer science related discipline.
• Programming fluency in C/C++ and/or Fortran with a deep understanding of software design, programming techniques, and algorithms.
• Strong mathematical fundamentals, including linear algebra and numerical methods.
• Experience with parallel programming, ideally CUDA C/C++ and OpenACC.

Ways To Stand Out From The Crowd

• Domain expertise in data and graph analytics, signal processing, telecommunications, geographic information systems, machine learning, or deep learning.
• Experience working within the Federal Government and the ability to hold a US security clearance.

Compensation and Benefits

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 - 218,500 USD for Level 3. You will also be eligible for equity and benefits.

Application Deadline

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

About NVIDIA's Culture

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!

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.

Key skills/competency

• GPU Acceleration
• C/C++ Programming
• Fortran
• Parallel Programming (CUDA, OpenACC)
• Algorithm Optimization
• Data Structures
• Linear Algebra
• Numerical Methods
• Deep Learning
• Public Sector Domain Expertise