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 @ 6
GPU @ 4
HPC
Profiling @ 6
- 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 developing performance tools for GPUs that serve both newcomers and advanced 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, with a focus on AI applications.
- Build tools used by CUDA developers worldwide.
- Collaborate with NVIDIA teams, including the compiler and CUDA driver teams, to influence and design new features from the ground up.
Requirements
- 5+ years of software engineering experience, with a focus on performance tools.
- Bachelor's degree in Electrical Engineering, Computer Science, or equivalent experience.
- Strong programming skills in C++.
- Existing knowledge of GPU hardware or motivation to learn.
Preferred Qualifications
- Expertise in CUDA kernel programming and profiling.
- Knowledge of parsing DWARF.
- Motivation to apply existing knowledge and learn new skills in a fast-paced environment.
- Outstanding interpersonal skills and the ability to collaborate effectively as part of a dynamic team.
Benefits
- Base salary range of $152,000–$241,500 for Level 3, or $184,000–$287,500 for Level 4, depending on location, experience, and compensation for similar positions.
- Eligibility for equity and benefits.
- NVIDIA is committed to an inclusive work environment and is an equal opportunity employer.
Applications will be accepted at least until October 24, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
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