Jobs
Benefits & Perks
•Team events and activities
•Competitive salary and equity package
•Comprehensive health, dental, and vision insurance
•Parental leave
•Generous paid time off and holidays
•Professional development budget
•Equity
•Healthcare
•Parental Leave
•Learning
Required Skills
JavaScript
Node.js
Python
About the Role
NVIDIA is hiring passionate, world-class computer scientists and engineers to work in its Public Sector Developer Technology (Devtech) team! In this 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.
Responsibilities
- Work directly with key application developers to understand the current and future problems they are solving
- Craft and optimize core parallel algorithms and data structures to provide the best solutions using GPUs, through reference code development
- Contribute directly to the full software stack including libraries, applications, and high productivity software environments (e.g. Python)
- Collaborate 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
- Investigate the impact on application performance and developer productivity
- Occasional travel from time to time for conferences and on-site visits with developers
Required Qualifications
- MS or PhD degree or equivalent experience in an engineering or computer science related field
- Programming fluency in C/C++ with a deep understanding of software design, programming techniques, and algorithms
- Strong computer science fundamentals, including parallel data structures and algorithms, combinatorics, and sparse representations
- 5+ years of relevant work experience with parallel programming, ideally CUDA C/C++, OpenMP or MPI, or SHMEM (OpenSHMEM or NVSHMEM)
Preferred Qualifications
- Domain expertise in data and graph analytics, data-science, network analysis, cybersecurity, machine learning, or deep learning
- Experience developing with libraries in the RAPIDS ecosystem, including but not limited to cuDF, cuML, cu Graph, Spark and cuPY
- Experience with JIT compilation and using NUMBA
- Background with algorithm and architecture codesign
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 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!
Compensation and Benefits
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
- Level 4: $184,000 USD - $287,500 USD
- Level 5: $224,000 USD - $356,500 USD
You will also be eligible for equity and benefits.
Additional Information
- Work Type: Hybrid (#)
- Application Deadline: Applications will be accepted at least until January 13, 2026
- Position Status: This posting is for an existing vacancy
- Recruiting Process: NVIDIA uses AI tools in its recruiting processes
Equal Opportunity
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

NVIDIA
PublicA computing platform company operating at the intersection of graphics, HPC, and AI.
10,001+
Employees
Santa Clara
Headquarters
$4.57T
Valuation
Reviews
4.1
10 reviews
Work Life Balance
3.5
Compensation
4.2
Culture
4.3
Career
4.5
Management
4.0
75%
Recommend to a Friend
Pros
Great culture and supportive environment
Smart colleagues and excellent people
Cutting-edge technology and learning opportunities
Cons
Team-dependent experience and outcomes
Work-life balance issues with long hours
Politics and influence over competence
Salary Ranges
47 data points
Junior/L3
Mid/L4
Junior/L3 · Analyst
7 reports
$170,275
total / year
Base
$130,981
Stock
-
Bonus
-
$155,480
$234,166
Interview Experience
7 interviews
Difficulty
3.1
/ 5
Experience
Positive 0%
Neutral 86%
Negative 14%
Interview Process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Interview
5
System Design Interview
6
Team Review
Common Questions
Coding/Algorithm
System Design
Technical Knowledge
Behavioral/STAR
News & Buzz
Negotiating NVIDIA's Offer
Base, stock, and sign-on negotiable. Recruiters invested in closing candidates. CEO reviews all 42K employee salaries monthly. Stock growth has made many employees millionaires.
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NaNw ago
NVIDIA Company Reviews
WLB rated 3.9/5 (lowest category). 64% satisfied with WLB but 53% feel burnt out. Compensation rated 4.4-4.5/5. Experience highly team-dependent.
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NaNw ago
NVIDIA Culture Discussions
Team-dependent experience; sink-or-swim culture that rewards high performers but can be overwhelming. No politics, flat structure, but demanding workload with some teams requiring evening/weekend work.
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·
NaNw ago
NVIDIA Interview Discussions
Technical bar is high with 4-6 rounds. Process takes 4-8 weeks. Expect C++ questions, LeetCode medium, and system design. Difficulty rated 3.16/5.
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