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This listing was closed on Oct 16, 2026.
Browse Open JobsSenior Machine Learning Engineer - AV Core
Summary by AIEngineer.careers
Senior Machine Learning Engineer - AV Core is a Machine Learning Engineer role (full-time). with Wayve. in GREATER LONDON, GB. Imported listing (source: mydailyaijobs.com). Apply on the employer's site (mydailyaijobs.com).
Imported listing (source: mydailyaijobs.com) · Apply on mydailyaijobs.com
GREATER LONDON · GB
—
Full-time
SENIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from mydailyaijobs.com
Wayve is seeking a Senior Machine Learning Engineer to lead large-scale data curation and mining for their autonomous vehicle (AV) core models. The role focuses on enabling robust driverless operation through model introspection, rare event mining, and out-of-distribution detection mechanisms. You will work at the intersection of model engineering, infrastructure, and data, collaborating closely with research and applied engineering teams.
Responsibilities
- Lead large-scale data enrichment, curation, and hard/rare event mining workflows.
- Design and train out-of-distribution detection mechanisms for robust AV performance.
- Build reliable ML training and evaluation systems using Python and PyTorch.
- Collaborate across Pre/Midtraining, reward modelling, and Data Enrichment Platform teams.
- Improve efficiency of the ML and operations stack through architectural decisions.
Requirements
- Hands-on experience with ML systems deployed in the real world.
- Proficiency in Python and PyTorch with strong software engineering practices.
- Strong track record in ML operations, distributed computing, and large-scale inference.
- Senior-level ownership with ability to lead technical areas and collaborate across boundaries.
Wayve
Greater London · GB · 750+ employees
Wayve specializes in end-to-end embodied AI solutions for autonomous vehicles, aiming to provide safe and adaptable driving intelligence. Unlike traditional systems reliant on rigid mapping, its technology learns from real-world data and simulations to operate in complex environments.
