Senior AI Training Performance Architect-Optimization Lead

Nvidia Corporation; Santa Clara (CA); On-site; USD 184,000 - 356,500; Full time

Job summary

NVIDIA in Santa Clara, CA, seeks a Senior AI Training Performance Architect to optimize AI training workloads on state-of-the-art hardware and software stacks.

You will analyze bottlenecks, implement production-quality software across the DL platform, contribute to MLPerf submissions, and develop tools for workload analysis and automation, shaping future architectures for scalable AI training.

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.

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.

Skills

Deep learning

Neural networks

Computer architecture

Performance analysis

CUDA

C++

Python

Education

PhD in CS/EE/CSEE

MS with 8+ years experience

Tools

CUDA

DL frameworks

System simulators

Job description

NVIDIA in Santa Clara, CA, seeks a Senior AI Training Performance Architect to optimize AI training workloads on state-of-the-art hardware and software stacks.

You will analyze bottlenecks, implement production-quality software across the DL platform, contribute to MLPerf submissions, and develop tools for workload analysis and automation, shaping future architectures for scalable AI training.