Staff Tech Lead: Offline Vision & Evaluation ML

Wayve

Greater London

Hybrid

GBP 140,000 - 180,000

Full time

14 days+
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Benefits offered by this job

Hybrid work environment

Job summary

Wayve in London is seeking a Staff Tech Lead Manager for the Measurement team in AI Evaluation to build and productionise offline scene understanding models. You will manage four Senior MLEs, define technical direction for turning on-vehicle models and Wayve Foundation Models into robust, scalable solutions, and align with teams in the UK and US.

This full-time, hybrid role offers collaboration across AV Core, Foundation Model teams, Evaluation, and Model Development Platform, with a focus on

Qualifications

  • 8+ years in ML engineering with CV experience and production ML systems shipping.
  • 2+ years line-management or tech-leading senior engineers.
  • Staff-level technical depth in transformer-based and multimodal architectures.
  • Proficient in Python and PyTorch; production-grade ML systems.
  • Strong cross-functional leadership across teams and geographies.

Responsibilities

  • Lead and grow the London team of Senior MLEs and hire as scope grows.
  • Define technical direction for offline measurement using shared models.
  • Own the roadmap with sprint, quarterly, and annual cadences.
  • Drive production quality with robust, generalisable ML architectures.
  • Accelerate the AV development loop with faster iteration feedback.
  • Coordinate with UK/US teams to align roadmaps and investment.

Skills

ML engineering
Computer vision
Line management
Technical depth
Python
PyTorch
Cross-functional leadership

Education

MS or PhD in CS/Engineering

Tools

PyTorch

Job description

Wayve in London is seeking a Staff Tech Lead Manager for the Measurement team in AI Evaluation to build and productionise offline scene understanding models. You will manage four Senior MLEs, define technical direction for turning on-vehicle models and Wayve Foundation Models into robust, scalable solutions, and align with teams in the UK and US.

This full-time, hybrid role offers collaboration across AV Core, Foundation Model teams, Evaluation, and Model Development Platform, with a focus on

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