Senior AI Training Performance Architect
NVIDIA· Architect
Santa Clara, CA$184k - $287.5kfull-timePosted 2mo ago
About the role
Senior engineer focused on performance analysis and optimization across hardware/software stack to maximize AI training performance on state-of-the-art NVIDIA platforms.
Responsibilities
- Understand, analyze, profile, and optimize AI training workloads on state-of-the-art hardware and software platforms.
- Identifying performance bottlenecks of AI training on GPUs, prioritizing and then solving problems across the key AI training workloads.
- Implement production-quality software across multiple layers of NVIDIA's deep learning platform stack, from drivers to DL frameworks.
- Build and support NVIDIA submissions for MLPerf Training benchmarks.
- Implement key DL 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.
Qualifications
- PhD in CS, EE or CSEE (or equivalent experience) with 5+ years of relevant experience; or MS with 8+ years of experience.
- Strong background in deep learning and neural networks, particularly in 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 programming with C++, Python, and CUDA.
Skills
Required:AI training performance optimizationC++PythonCUDA
Benefits
- equity
- benefits (see benefits link)
Last updated Jul 31, 2026. Interested? Apply on the company site.
About NVIDIA
World Leader in AI Computing
NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.
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