Hybrid London Staff Tech Lead — ML Vision Models

AI Startups UK; Greater London; Hybrid; GBP 110,000 - 150,000; Full time

Benefits offered by this job

Hybrid work policy

Job summary

Wayve in London seeks a Staff Tech Lead Manager for the Measurement team to lead four Senior MLEs and shape the offline scene understanding work. You will steer the technical direction turning on-vehicle and foundation models into robust, scalable offline predictors, guiding evaluation and validation across UK/US teams.

The role emphasizes measurement-driven development, epoch planning, and collaboration with AV Core, Evaluation, and Simulation teams to inform model improvements and customer

Qualifications

• 8+ years in ML engineering, including hands-on computer vision with camera and/or lidar data.
• 2+ years line-managing or tech-leading senior engineers.
• Staff-level technical depth in transformer-based and multimodal architectures and large-scale training.
• Proficient in Python and ML frameworks (especially PyTorch).
• Strong cross-functional leadership and roadmap alignment across teams.

Responsibilities

• Directly manage four Senior MLEs in London.
• Guide architecture for adapting on-vehicle models for offline measurement use.
• Own planning and roadmap from sprint to multi-year horizons.
• Maintain rigorous ML systems engineering practices in production context.
• Accelerate iteration by shortening model-to-feedback cycles.

Skills

ML engineering

Line management

Staff-level depth

Python

PyTorch

Education

MS or PhD in Computer Science/Engineering

Tools

PyTorch

Job description

Wayve in London seeks a Staff Tech Lead Manager for the Measurement team to lead four Senior MLEs and shape the offline scene understanding work. You will steer the technical direction turning on-vehicle and foundation models into robust, scalable offline predictors, guiding evaluation and validation across UK/US teams.

The role emphasizes measurement-driven development, epoch planning, and collaboration with AV Core, Evaluation, and Simulation teams to inform model improvements and customer