Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 7
API
CUDA
Communication @ 6
Data Science
Debugging @ 4
Deep Learning @ 7
GPU @ 7
Linux @ 4
Software Development @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
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, with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world.
NVIDIA is looking for a motivated systems software engineer with a deep understanding of device drivers and phenomenal C/C++ skills. This role will work on the CUDA Driver, a core component of NVIDIA's platform for accelerating general-purpose computation on the GPU. You will be an integral part of a team delivering features and improvements that realize the potential of NVIDIA hardware for workloads including deep learning, scientific computation, data science, self-driving cars, video games, and virtual reality.
Responsibilities
- Use design abilities, coding expertise, and creativity to deliver the best compute platform.
- Craft elegant solutions to complex problems and help shape the future direction of CUDA.
- Evangelize, architect, and implement new features.
- Coordinate and drive development efforts across multiple teams.
- Help define forward-looking improvements to the CUDA APIs and programming model.
- Write effective, maintainable, and well-tested code.
- Develop code for multiple operating systems.
Requirements
- Bachelor's or master's degree in Computer Science, Electrical Engineering, or a related field, or equivalent experience.
- Strong C and C++ programming skills.
- Minimum of 7 years of related development experience; multiple positions for varying experience levels are open.
- Experience driving projects across multiple teams.
- Experience working with large codebases.
- Background with operating-system interfaces for threads, process control, and virtual memory.
- Experience writing and debugging multithreaded programs.
- Good written communication and presentation skills.
Preferred Qualifications
- Prior experience with parallel computing.
- Understanding of system-level architecture, including interconnects, memory hierarchy, interrupts, and memory-mapped I/O.
- Knowledge of memory coherence and consistency models.
- Background with kernel-mode development.
- Experience with Linux or Windows systems software development.
Compensation and Benefits
The base salary range is $184,000–$287,500 USD. The salary will be determined based on location, experience, and the pay of employees in similar positions. The role is also eligible for equity and benefits.
Applications will be accepted at least until July 1, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer committed to an inclusive work environment.