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
CUDA @ 4
GPU @ 4
HPC
Profiling @ 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 Nsight Compute helps CUDA engineers innovate in artificial intelligence and high-performance computing. Join the team to develop performance tools for GPUs that support both newcomers and experienced CUDA experts. Your contributions will help shape profiling tools and enable engineers to harness the full power of GPU technology.
Responsibilities
- Design and implement innovative features for GPU performance profiling tools.
- Collaborate with teams across NVIDIA, including the GPU hardware team, compiler team, and other developer tools teams.
- Apply your knowledge and skills to build tools used by CUDA developers worldwide.
Requirements
- 8+ years of proven software engineering experience, with a focus on performance tools.
- Bachelor’s degree in Electrical Engineering or Computer Science, or equivalent experience.
- Strong programming skills in C++.
- Existing knowledge of GPU hardware or motivation to learn and collaborate closely with hardware teams on the design, bring-up, and productization of new profiling features.
Preferred Qualifications
- Expertise in CUDA kernel programming and profiling.
- Outstanding interpersonal skills and the ability to collaborate effectively as part of a dynamic team.
- High motivation to apply existing knowledge and learn new skills in a fast-paced environment.
Compensation And Benefits
The base salary range is USD 184,000–287,500 for Level 4 and USD 224,000–356,500 for Level 5. Compensation is determined based on location, experience, and the pay of employees in similar positions. The role also includes eligibility for equity and benefits.
Applications will be accepted at least until May 19, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is committed to fostering a diverse work environment and providing equal employment opportunities.