Tech Lead Manager, World Modeling

Wayve; City Of London; On-site; GBP 85,000 - 110,000; Full time

Job summary

A leading AI technology firm in London is seeking an experienced Tech Lead Manager to lead a team in advancing autonomous driving research. You will design and develop generative world models, mentor researchers, and drive cross-functional collaboration. Ideal candidates should have 5+ years in ML engineering, 2+ years in management, and expertise in generative modelling with strong communication skills. This role offers a dynamic environment focused on cutting-edge technology.

Qualifications

• 5+ years of experience in ML engineering or applied research roles.
• 2+ years of people management experience.
• Deep knowledge of generative modelling and supervised learning.
• Experience building large-scale ML infrastructure.

Responsibilities

• Architect the next generation of generative world models.
• Lead a high-performing team of applied researchers.
• Collaborate across teams for seamless integration of ML models.
• Coach and mentor team members.

Skills

ML engineering experience

People management

Generative modelling expertise

Python proficiency

Communication skills

Tools

PyTorch

Job description

Overview

At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital or civil status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.

Wayve is the leading developer of Embodied AI technology. Founded in 2017, our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate complex environments, enhancing the usability and safety of automated driving systems. Our vision is to create autonomy that propels the world forward. Our mapless, hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. We embrace uncertainty and complex challenges to unlock groundbreaking solutions, while staying humble and focused on excellence. We value diversity, embrace new perspectives, and foster an inclusive work environment where contributions matter.

Make Wayve the experience that defines your career.

The role

Science is the team advancing our end-to-end autonomous driving research. The team accelerates our journey to AV2.0 and incubates ideas with the potential to become game-changing technological advances for the company.

What this team is solving:

This role sits within Science, focusing on unlocking disruptive innovation that solves self-driving. The Accelerated Learning Loop (ALL) team aims to dramatically reduce dependency on expensive and time-consuming on-road data collection by building the next generation of world modelling and world planner solutions. Generative simulation solutions (with models like GAIA-2) will accelerate training, testing, and deployment of autonomous driving systems, especially in new geographies and unseen conditions.

Areas of focus include:

• Building the next generation of world models to reconstruct and generate realistic, diverse, and temporally consistent driving scenes.
• Developing driving models by combining real and synthetically generated data.
• Improving evaluation capabilities with higher quality, scale and predictive power of models.

Impact & role expectations

As Tech Lead Manager, you will lead a high-performing team of applied researchers and help answer bold, open questions about deploying autonomous driving in new geographies and leveraging synthetic data for evaluation and training.

• How quickly can we deploy autonomous driving in a geography where we've never collected AV data?
• Can synthetically generated data fully replace on-road data for evaluation and training?

Key responsibilities

Technical Contributions & Leadership

• Architect the future – design and evolve the next generation of generative world models and driving models, setting a high technical bar for quality and innovation.
• Accelerate research impact – partner with applied researchers to develop and iterate on novel model recipes that drive progress from experimentation to production impact.
• Get hands-on when it matters – lead from the front by contributing directly to key system components, codebases, and experiments, especially during high-leverage moments.
• Disrupt thoughtfully – challenge assumptions, ask sharp questions, and champion bold ideas that push beyond incremental gains.

Team Management & Cross-Functional Execution

• Make things happen – lead a cross-functional team of applied scientists and ML engineers across ML, simulation, and evaluation; drive quarterly planning and execution of research-engineering initiatives for rapid iteration in ambiguous environments.
• Align and connect – collaborate across teams to ensure seamless integration of ML models into the broader stack; manage upwards and laterally to align goals with priorities and unblock dependencies.
• Architect teams – grow and structure a resilient team by hiring top talent, designing operating models, and fostering an inclusive culture; establish rituals and recognition practices that celebrate performance and inclusion.
• Level up – coach and mentor team members with growth plans aligned to individual strengths and aspirations; lead by example with technical engagement and clear feedback.
• Champion change – guide the team through evolving research priorities and fast-moving execution, communicating changes effectively while maintaining stability and trust.

About you

We’re looking for the following skills and experience to set you up for success as a Tech Lead Manager at Wayve.

Essential

• 5+ years of experience in ML engineering or applied research roles.
• 2+ years of people management experience, including direct reports and cross-functional project ownership.
• Deep knowledge of generative modelling (e.g., auto-regressive, diffusion, VAEs) and supervised learning.
• Experience building large-scale ML infrastructure and working with high-dimensional temporal data (video, sensor fusion).
• Strong Python and PyTorch engineering fundamentals, with experience building research-grade production tools.
• Track record of delivering ML systems that translate into product or platform wins.
• Excellent communication skills and a passion for coaching and mentoring others.
• Balance technical depth with people leadership; know when to lead from the front and when to empower the team.
• Ability to embrace ambiguity and maintain clarity and momentum through uncertainty.
• Systems thinker who builds scalable team structures, rituals and career development frameworks.

Nice to have

• Experience in AVs, robotics, simulation, or other embodied AI domains.
• Experience with reward modeling, evaluation benchmarks, or synthetic-to-real transfer.
• Strong publication record or contributions to open-source ML tooling.
• Previous startup-like or high-ambiguity environment experience.

What this role may not be for

• Hands-on technical problem solving is your strengths, rather than mentoring and leading a team.
• You prefer to stay hands-on and would rather code than manage and guide others.
• You are comfortable with high-ambiguity, research-adjacent projects with evolving targets.
• You have not managed a team through full-cycle planning, delivery, and feedback loops.

We understand that not everyone will meet all requirements. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact, we encourage you to apply.

For more information visit Careers at Wayve. To learn more about what drives us, visit Values at Wayve.

DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any job adverts or interviews. However, we may collect information about care responsibilities and disabilities as part of an optional DEI Monitoring form to help identify areas of improvement in our hiring process and ensure inclusivity and non-discrimination.