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
API @ 3
CUDA @ 6
Debugging @ 6
Deep Learning @ 3
Distributed Systems @ 3
GPU @ 3
Leadership @ 6
Mentoring @ 6
OpenCL @ 3
OpenGL @ 3
PyTorch @ 3
TensorFlow @ 3
vLLM @ 3
- 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
We are looking for a software engineering manager with strong leadership and mentoring skills to join the CUDA Driver team. The team designs the CUDA programming model, exposes it through the CUDA Driver and CUDA Runtime APIs, and implements the associated functionality. The CUDA Driver and its programming model serve as the foundation for NVIDIA's CUDA-X software stack and compute platform. The team primarily works on the CUDA Driver memory model, including how to allocate, move, and access memory efficiently across NVIDIA's hardware offerings in both single-node and multi-node environments.
Responsibilities
- Lead a team of system software engineers to design and build CUDA for current and future hardware architectures.
- Collaborate with teams across NVIDIA to define and drive CUDA's roadmap.
- Contribute to CUDA feature design and drive adoption of new CUDA functionality.
- Establish team objectives, prioritize incoming work, mentor team members, and manage team performance.
- Monitor team execution, identify opportunities for process improvement, and lead implementation of improvements.
Requirements
- 8+ years of overall experience in the software industry, including 3+ years of management experience.
- Bachelor's, master's, or Ph.D. degree, or equivalent experience, in Computer Science, Computer Engineering, or a related field.
- Strong system software fundamentals, hands-on C programming, and debugging skills.
- Ability to manage a team's execution toward project deliverables, particularly in environments with competing priorities.
Preferred Qualifications
- In-depth understanding of computer architecture and memory subsystems.
- Experience implementing or directly using GPU programming APIs such as CUDA, OpenCL, OpenGL, or Vulkan.
- Background with distributed systems or high-performance clusters.
- Experience with deep learning frameworks such as PyTorch, TensorFlow, or vLLM.
Compensation and Benefits
The base salary is determined based on location, experience, and the pay of employees in similar positions. The base salary ranges are:
- Level 3: USD 224,000–356,500 per year
- Level 4: USD 272,000–431,250 per year
The position is also eligible for equity and benefits. Applications will be accepted at least until September 19, 2026. NVIDIA uses AI tools in its recruiting processes. NVIDIA is an equal opportunity employer committed to fostering an inclusive work environment.