Senior AI Training Performance Architect

at Nvidia

📍 Santa Clara, United States

USD 184,000-356,500 per year

SENIOR

✅ On-site

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 @ 4 CUDA @ 6 Deep Learning @ 7 GPU @ 6 Performance Analysis Python @ 6

Details

NVIDIA is seeking a senior engineer focused on performance analysis and optimization for AI training workloads. The role involves working across the hardware and software stack, from GPU architecture to application code, to achieve peak performance and influence NVIDIA's hardware and software roadmap.

Responsibilities

Understand, analyze, profile, and optimize AI training workloads on state-of-the-art hardware and software platforms.
Identify performance bottlenecks in AI training on GPUs, prioritize issues, and solve problems across key AI training workloads.
Implement production-quality software across multiple layers of NVIDIA's deep learning platform stack, from drivers to deep learning frameworks.
Build and support NVIDIA submissions for MLPerf Training benchmarks.
Implement key deep learning training workloads in NVIDIA's proprietary processor and system simulators to enable future architecture studies.
Develop tools to automate workload analysis, optimization, and other critical workflows.

Requirements

PhD in Computer Science, Electrical Engineering, or Computer Science and Engineering, or equivalent experience, with 5+ years of relevant experience; or a master's degree with 8+ years of experience.
Strong background in deep learning and neural networks, particularly training.
Solid understanding of computer architecture and familiarity with GPU architecture fundamentals.
Proven background in analyzing and tuning application performance.
Proven experience with processor- and system-level performance modeling.
Proficiency in C++, Python, and CUDA.

Benefits

Equity and benefits are provided.
NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer.

Compensation

The base salary depends on location, experience, and the pay of employees in similar positions. The stated base salary ranges are $184,000–$287,500 for Level 4 and $224,000–$356,500 for Level 5.

Applications will be accepted at least until July 28, 2026. This posting is for an existing vacancy.