LLM Training Performance Engineer

NVIDIA Corporation; Santa Clara (CA); On-site; USD 124,000 - 242,000; Full time

Benefits offered by this job

Equity

Benefits package

Job summary

NVIDIA Corporation is seeking researchers to understand, profile, and optimize AI training workloads on innovative GPU platforms in Santa Clara, CA. You will contribute to training performance across leading LLMs and implement production-ready software across multiple layers of the NVIDIA deep learning stack.

The role requires a strong background in deep learning, GPU architecture, and proficiency in C++, Python, and CUDA. Equity and comprehensive benefits accompany a competitive base salary.

Qualifications

• MS or PhD in Computer Science, Electrical Engineering or Computer Engineering (or equivalent experience).
• Strong background in deep learning and neural networks, especially model training optimisations.
• A deep background in computer architecture and fundamentals of GPU architecture.
• Proven experience analysing and tuning application performance & processor and system-level performance modeling.
• Programming skills in C++, Python, and CUDA.

Responsibilities

• Understand, analyze, profile, and optimize AI training workloads on innovative hardware and software platforms.
• Understand the big picture of training performance on GPUs, prioritizing and solving problems across state-of-the-art LLMs.
• Implement production-quality software in multiple layers of NVIDIA's deep learning platform stack.
• Implement key LLM training workloads in NVIDIA's proprietary processor and system simulators to enable future architecture studies.
• Build agentic tools to automate workload analysis, workload optimization, and other critical workflows.

Skills

C++

Python

CUDA

Deep learning

Performance analysis

Computer architecture

Education

MS/PhD in CS/EE/CE or equivalent experience

Tools

CUDA Toolkit

Job description

NVIDIA Corporation is seeking researchers to understand, profile, and optimize AI training workloads on innovative GPU platforms in Santa Clara, CA. You will contribute to training performance across leading LLMs and implement production-ready software across multiple layers of the NVIDIA deep learning stack.

The role requires a strong background in deep learning, GPU architecture, and proficiency in C++, Python, and CUDA. Equity and comprehensive benefits accompany a competitive base salary.