Wayve
Staff ML Performance Engineer (Training Efficiency)
Sunnyvale, California USA · Staff+ · Full-time
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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
- 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
Compensation
- 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.
Benefits
- BS or MS in Machine Learning, Computer Science, Engineering, or a related technical discipline or equivalent experience
Company info
- 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.
- In order to set you up for success in this role, we're looking for the following skills and experience.
This listing is sourced directly from Wayve's careers page and normalized into a canonical job model.