Principal ML Engineer — Autonomous Driving, Hybrid

Wayve; Greater London; Hybrid; GBP 120,000 - 160,000; Full time

Benefits offered by this job

Equity

Relocation support

Hybrid working

Learning & development budget

Health insurance

Dental

Parental leave

Job summary

Wayve is seeking a highly technical, hands-on Lead Engineer to own the end-to-end Driving model within our Driving Product Team. You will code and run experiments while guiding a small team and shaping data and model iterations used in our L2 deployment with OEM partners like Nissan and Mercedes.

You will balance hands-on development with leadership, drive cross-functional collaboration across data, model, and vehicle interface domains, and maintain a strong focus on production readiness and

Qualifications

• Hands-on with Python and model/data iteration.
• Experience deploying ML models in production.
• Experience shipping ML for embodied AI applications.
• Production-focused rather than pure research.
• Strong IC or tech-lead background.

Responsibilities

• Lead the team iterating on L2 driving performance, balancing hands‑on technical work with team leadership.
• Diagnose the highest impact issues on the road, root cause them, and resolve them through data and model iteration.
• Own changes to data recipes, model architecture, evaluation and release readiness for the driving model.
• Partner with other teams to resolve cross-functional issues, including model and vehicle interface problems.
• Act as one of the team's key hands‑on developers, writing code and running experiments alongside directing the team's priorities.

Skills

Python

Production ML

Hands-on leadership

Embodied AI

Tech lead

Job description

Wayve is seeking a highly technical, hands-on Lead Engineer to own the end-to-end Driving model within our Driving Product Team. You will code and run experiments while guiding a small team and shaping data and model iterations used in our L2 deployment with OEM partners like Nissan and Mercedes.

You will balance hands-on development with leadership, drive cross-functional collaboration across data, model, and vehicle interface domains, and maintain a strong focus on production readiness and