ML Performance Engineer — Optimize GPU Training at Scale

NVIDIA Corporation; Santa Clara (CA); On-site; USD 224,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a dedicated Software Engineer, ML Performance to join our Santa Clara team. You will optimize performance for distributed training and inference at scale across GPUs, working with cutting-edge AI technologies.

The role requires deep Python and CUDA, and experience across multiple stack layers. You will collaborate with build partners, define metrics, and help drive product roadmaps.

Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.
• 12+ years of software engineering experience, including hands-on optimization of GPU training or inference workloads.
• Experience diagnosing performance across many jobs, machines or tenants with baseline, evidence and outcome.

Responsibilities

• Analyze the performance of distributed training and inference across the stack.
• Identify bottlenecks, propose solutions with supporting evidence.
• Define performance metrics tracked across a fleet of GPUs.
• Break metrics into signals engineers can debug.
• Decide which signals to collect first and drive regression analysis.
• Evaluate automated diagnoses and ensure accuracy of findings.

Skills

Python

CUDA

Performance optimization

Distributed systems

GPU training/inference

PyTorch

Education

Bachelor's degree in CS/CE or related field

Job description

NVIDIA is seeking a dedicated Software Engineer, ML Performance to join our Santa Clara team. You will optimize performance for distributed training and inference at scale across GPUs, working with cutting-edge AI technologies.

The role requires deep Python and CUDA, and experience across multiple stack layers. You will collaborate with build partners, define metrics, and help drive product roadmaps.