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Staff ML Performance Engineer (Training Efficiency)

Wayve

Sunnyvale, California USA·$336,400 - $359,000

$336,400 - $359,000

senior

On-siteSoftware engineering

Source checked 3 hours ago.

Posted 7 months ago.

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Before the detail, here's the challenge you'd help us solve.

We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that.

Here's what this particular role covers.

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

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