Skip to main content
Back to jobs

Staff ML Performance Engineer (Training Efficiency)

External
Wayve logoWayve · Sunnyvale
$336K–$359K/yrFull-timeOn-site3mo ago
Machine LearningObservabilityPerformance OptimizationPython
Cover LetterConnect

Prepare for this interview

Elite

AI-generated questions, company research, and talking points tailored to this role


About the role

We are looking for a Staff ML Performance Engineer to join our Training Tech team working on optimizing large scale ML jobs to enable scaling our models to the next order of magnitude. A successful candidate will increase efficiency of training and inference workloads in order to allow Wayve to train larger models faster.

Responsibilities

  • Profile ML workloads to identify their bottlenecks, e.g. using NVIDIA Nsight Systems
  • Design and implement efficiency improvements to maximize MFU and throughput, e.g. parallelism, model compilation, mixed precision
  • Design and implement observability tools to identify bottlenecks and drive performance improvements, e.g. to track MFU, throughput, latency, etc
  • Design and implement benchmarking tools, e.g. to track efficiency gains or regressions
  • Collaborate closely with Research teams to integrate training efficiency improvements and create a culture of performance optimization
  • About you
  • In order to set you up for success in this role, we're looking for the following skills and experience.
  • Essential
  • 10+ years of industry experience driving performance engineering across ML systems, GPU compute infrastructure, distributed platforms or similar field.
  • Experience optimizing large scale jobs on GPU compute clusters.
  • Experience in working in platform teams and working with research teams.
  • Experience in writing, reporting, and tracking performance benchmarks in an open and accessible way.
  • Ability to write high quality, well-structured and tested Python code
  • BS or MS in Machine Learning, Computer Science, Engineering, or a related technical discipline or equivalent experience
  • Desirable
  • Experience working with concurrent, parallel and distributed computing.
  • Experience using NVIDIA NSight Systems or other system profilers.
  • Experience implementing GPU kernels (CUDA, Triton, etc).
  • Knowledge of computing fundamentals - what makes code fast, secure and reliable.
  • This role is a full-time role based in Sunnyvale, CA (hybrid) and the reasonably estimated salary for this role ranges from $336,400 to $359,000, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience.
  • #LI-HH1

Benefits

Equity / stock options

Your Match

How well this role fits your profile.

Company Intel

What employees say

Worked at Wayve? Share your experience

Interested in this role?

Apply on the company's website.

Cover LetterConnect