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.
API
CUDA
Communication @ 6
Debugging @ 4
Deep Learning
GPU
Linux @ 4
macOS @ 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
Work on the CUDA driver and runtime, core components of NVIDIA's platform for accelerating general-purpose computation on GPUs. The team analyzes application performance, investigates software and hardware bottlenecks, and delivers features and improvements for workloads including deep learning, scientific computation, self-driving cars, video games, and virtual reality.
CUDA defines a unified programming model across system configurations and hardware capabilities. The CUDA driver interacts with GPU hardware, kernel-mode drivers, and operating systems.
Responsibilities
- Evangelize, architect, and implement new features.
- Oversee and drive development efforts across multiple teams.
- Analyze full-stack performance across application-level software, libraries, system software, kernel software, and hardware.
- Define forward-looking improvements to CUDA APIs and the programming model.
- Create novel system software optimizations.
- Write effective, maintainable, and well-tested code.
- Develop code for multiple operating systems.
- Investigate complex performance problems and deliver robust solutions that accelerate applications.
- Collaborate with peers across NVIDIA to shape the future direction of CUDA.
Requirements
- Bachelor's or master's degree in Computer Science, Electrical Engineering, or equivalent experience.
- 7+ years of related development experience.
- Strong C programming skills.
- Experience working with large codebases.
- A track record of debugging performance problems in complex environments involving software and hardware components.
- Experience with operating system interfaces for threads, process control, and virtual memory.
- Experience writing and debugging multithreaded programs.
- Deep understanding of technology and passion for the work.
- Strong collaborative and interpersonal skills, including the ability to guide and influence effectively within a dynamic matrix environment.
- Good written communication skills.
Preferred Qualifications
- Understanding of system-level architecture, including interconnects, memory hierarchy, interrupts, and memory-mapped I/O.
- Experience tuning the performance of device drivers or low-level system software.
- Experience optimizing performance across CPU architectures such as x86, POWER, and ARM.
- Knowledge of memory coherence and consistency models.
- Experience with Windows, Linux, or macOS driver development.
Compensation and Benefits
- Base salary for Level 4: USD 184,000–287,500 per year.
- Base salary for Level 5: USD 224,000–356,500 per year.
- Eligible for equity and benefits.
- Applications will be accepted at least until July 28, 2026.
- NVIDIA is an equal opportunity employer committed to an inclusive work environment.
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