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. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. Now, NVIDIA’s GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world.
We are now looking for a passionate Software Engineer to design, develop, and productize NVIDIA's autonomous driving solutions. As a member of our perception team, you will build world-class perception solutions. You will design and implement perception SW component and be challenged to improve robustness, efficiency, reusability of the software component working closely with the world class perception engineers and researchers.
What you'll be doing:
Execute full software development life cycle (SDLC).
Write well-designed, testable code.
Integrate perception (but not limited) software components into a fully functional software system.
Develop software verification plans and quality assurance procedures.
Document and maintain software functionality.
Solve, debug and upgrade existing systems.
Stay in sync with project plans and industry standards
Deploy state-of-the art perception DNN models to embedded platforms.
Analyze and improve the system using both real and synthetic benchmark data.
What we need to see:
BS, MS or PhD in Computer Science or related fields (or equivalent experience).
Proven work experience (12+ years) on embedded platforms for real-time applications as a Software Engineer or Software Developer
Strong programming skills in C++ and Python.
Experience with test-driven development.
Experience with disciplined, design based approach to software development.
Proficiency in software engineering tools.
Ability to document requirements and specifications.
Outstanding communication and collaboration skills as we work as a tightly-knit team, always discussing and learning from each other.
Ways to stand out from the crowd:
Experience with CUDA / SIMD
Hands on background in deploying DNN models to embedded platforms for real-time applications.
Hands-on experience in using simulated / synthetic data to improve accuracy of machine learning models.
Background with deep learning framework (e.g., TensorFlow, PyTorch, etc).
Experience with integration and testing on real hardware / robotic platforms
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!
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 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.Skills Required
- Bachelor’s, master’s, or doctoral degree in Computer Science or a related field, or equivalent experience
- 12 or more years of professional experience developing software for embedded platforms and real-time applications
- Strong programming skills in C++ and Python
- Experience with test-driven development
- Experience using a disciplined, design-based software development approach
- Proficiency with software engineering tools
- Ability to document requirements and specifications
- Strong communication and collaboration skills
- Experience with CUDA or SIMD
- Experience deploying deep neural network models to embedded platforms for real-time applications
- Experience using simulated or synthetic data to improve machine learning model accuracy
- Experience with deep learning frameworks such as TensorFlow or PyTorch
- Experience integrating and testing software on real hardware or robotic platforms
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.
-
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.
-
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.
-
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.”
.png)
