Staff ML Performance Engineer (Training Efficiency)

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.

Key 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.

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