Tech Lead Manager, World Modeling

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. Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.

Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.

The role Science is the team that is advancing our end-to-end autonomous driving research. The team's mission is to accelerate our journey to AV2.0 and ensure the future success of Wayve by incubating and investing in new ideas that have the potential to become game-changing technological advances for the company.

What this team is solving: This role would sit within Science, focusing on unlocking disruptive innovation that solves self-driving. The team you will focus on, Accelerated Learning Loop (ALL), 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 that we can trust will accelerate training, testing, and deployment of autonomous driving systems, especially in new geographies and unseen conditions.

These are some areas the team is focused on:

• Building the next generation of world models to reconstruct and generate realistic, diverse, and temporally consistent driving scenes.
• Building the next generation of driving models by developing recipes that combine real and synthetically generated data.
• Evolving our evaluation capabilities by improving the quality, scale and predictive power of our models.

Where you'll have impact: As Tech Lead Manager, you'll lead a high-performing team of applied researchers and help us answer bold, open questions like: 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:

• 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 closely 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 us beyond incremental gains and toward breakthrough advances.

• Make things happen - Lead a high-performing, cross-functional team of applied scientists and ML engineers working across ML, simulation, and evaluation.
• Drive quarterly planning and execution of research-engineering initiatives, enabling rapid iteration and delivery in high-ambiguity environments.
• Align and connect - Collaborate across teams to ensure seamless integration of ML models into our broader stack.
• Manage upwards and laterally to align your team's goals with company priorities, and proactively unblock dependencies with clarity and purpose.
• Architect teams - Grow and structure a resilient team by hiring top talent, designing effective operating models, and fostering a sense of belonging-regardless of location.
• Create equitable rituals and recognition practices that celebrate performance and inclusion.
• Cultivate a strong, inclusive team culture rooted in scientific rigor, collaboration, and curiosity.
• Level up - Coach and mentor team members, tailoring growth plans to individual strengths and aspirations.
• Lead by example through technical engagement and clear feedback, ensuring the team upholds a high bar for excellence.
• Champion change - Navigate your team through evolving research priorities and fast-moving execution environments.
• Help the team embrace new approaches, communicate change effectively, and maintain stability and trust through uncertainty.

About you: In order to set you up for success as a Tech Lead Manager at Wayve, we're looking for the following skills and experience.

• 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.
• You have deep knowledge of generative modelling (e.g., auto-regressive, diffusion, or VAEs), supervised learning.
• You have experience building large-scale ML infrastructure and working with high-dimensional temporal data (e.g., video, sensor fusion).
• You have strong Python and PyTorch engineering fundamentals, and experience building research-grade production tools.
• You have a track record of delivering ML systems that translate into product or platform wins.
• You have excellent communication skills and a passion for coaching and mentoring others.
• You balance technical depth with people leadership.
• You know when to lead from the front and when to empower your team.
• You embrace ambiguity and help your team make sense of it, keeping clarity and momentum through uncertainty.
• You are a systems thinker who builds scalable team structures, rituals and career development frameworks.

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

This role might not be for you if:

• You're at your best when solving complex technical problems hands-on, rather than leading through others via mentoring and team support.
• You are mainly managing teams and no longer hands-on in technical projects, and have no desire to get in the weeds/code again.
• You aren't comfortable working on high-ambiguity, research-adjacent projects with moving targets.
• You haven't yet managed a team with direct reports through full-cycle planning, delivery, and feedback loops.

If you're passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply.