Wayve
Staff Machine Learning Engineer, Vision Models
Sunnyvale, California USA · Staff+ · Full-time
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DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · San Jose-Sunnyvale-Santa Clara, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
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About the role
- Make the evidence credible - ensure benchmarked results are statistically defensible and fit to feed validation pipelines at scale and our broader safety cases, across the product portfolio.
- You will define ground truth and correctness criteria across a complex driving taxonomy, and turn them into automated benchmarks and evidence that our validation pipelines and safety cases can stand on.
- Offline is where the interesting headroom is: more compute per frame, larger foundation models, and access to both past and future temporal context that the vehicle never has.
Responsibilities
- Develop the models - build, train, and fine-tune the scene understanding models at the centre of Wayve's offline measurement, adapting on-vehicle architectures and Wayve Foundation Models for offline use.
- Drive accuracy and generalisation - improve model performance across vehicle platforms, geographies, and driving conditions
- Measure what you build - benchmark your models, set quality bars, and use metrics and error analysis to steer the next iteration
- treat measurement as the feedback that drives the modelling.
- Drive accuracy and generalisation - improve model performance across vehicle platforms, geographies, and driving conditions; diagnose failure modes and close the loop on blind spots.
Requirements
- Experience with offboard or offline modelling: auto-labelling, model distillation, temporal or world models, or other ways of exploiting compute that on-vehicle systems cannot.
- Experience with fleet-scale data and large-scale distributed training infrastructure.
Compensation
- The reasonably estimated salary for this role ranges from $370,040 to $407,330, plus a competitive equity package.
Benefits
- Exploit the offline environment - use the advantages the vehicle does not have: higher compute budgets, larger model capacity, bidirectional temporal context, and multi-task or joint representation learning.
- In order to set you up for success as a Staff Machine Learning Engineer at Wayve, we're looking for the following skills and experience.
Company info
- ABOUT YOU In order to set you up for success as a Staff Machine Learning Engineer at Wayve, we're looking for the following skills and experience.
- At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.
This listing is sourced directly from Wayve's careers page and normalized into a canonical job model.