Used Tools & Technologies
Not specified
Required Skills & Competences
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.
Python @ 6
Machine Learning @ 4
Parallel Programming @ 3
CUDA @ 4
GPU @ 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
We are now looking for a Senior Kernel Performance Architect for Deep Learning Software.
NVIDIA is seeking extraordinary architects to develop processor and system architectures that accelerate machine learning, data analytics and high-performance computing applications. This position offers the chance to create a meaningful impact in a dynamic, technology-focused company.
Responsibilities
- Craft GPU-accelerated system architectures that push the boundaries of deep learning performance.
- Prototype high-performance software for deep learning and data analytics workloads.
- Analyze, visualize, and optimize software performance using analytical models, simulators, and test suites.
- Collaborate closely across NVIDIA teams such as:
- CUDA Compiler teams to identify performance issues.
- AI/ML training and inference performance teams to identify and optimize critical deep learning layers.
- Hardware architecture performance teams to define expectations for emerging deep learning hardware features.
Requirements
- Master's or PhD in Computer Science, Electrical Engineering, Computer Engineering, or equivalent experience.
- 5+ years of relevant industry or research experience.
- Strong foundation in machine learning and deep learning fundamentals.
- Strong background in high-performance kernels (such as CUTLASS) and experience with math library performance analysis and profiling to identify bottlenecks.
- Fluency in programming languages such as Python, C, and C++.
- Experience and familiarity with GPU computing and parallel programming models.
- Firsthand work experience with analytical performance modeling, profiling, and analysis.
Compensation
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 218,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits.
Additional information
- Applications for this job will be accepted at least until January 17, 2026.
- This posting is for an existing vacancy.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer. They do not discriminate on the basis of protected characteristics.