Machine Learning Engineering Manager, ADAS

Job description

Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that. Here’s what this particular role covers. 🛠️ About our ADAS Team Our ADAS team is bringing Wayve’s end-to-end AI driving to production-grade advanced driver assistance, working directly with our OEM partners. Recent partnership deals mean we’re now delivering ADAS into production programs, and it’s one of Wayve’s top priorities. The team is scaling quickly, and the next 18 months will be focused on getting it right for the first SOP. This is a chance to sit at the heart of the work that drives Wayve’s upcoming business. 🧠 Your day-to-day - Splitting your time roughly 60% management and 40% hands-on, leading a team of around seven ML engineers, made up of new hires and an existing sub-team - Acting as tech lead across multiple workstreams, setting the vision for how problems get solved, in what order, and with which dependencies - Reviewing and approving delivery plans for the tasks you own - Partnering with TPMs on planning and execution, and with Product to help shape priorities - Coaching and developing the ML engineers on your team, supporting their growth as the team scales 🧩 What you’ll be working on: - Taking our end-to-end AI driving approach into ADAS for a specific OEM production programme - Bringing ML models from proof of concept through to production on embedded automotive hardware - Optimising runtime and inference so the right model runs well on constrained hardware, rather than defaulting to the biggest one - Building and scaling a new team during a high-priority growth phase, with plenty of room to shape how it works - Working across system boundaries with software, embedded and product teams to deliver a coherent product 👤 You should apply if: - Expert background in developing ML, specifically computer vision - You are/have been a people manager and enjoy developing engineers - You’ve worked across systems with software developers and product teams, particularly on embedded software - You have hands-on experience with embedded runtime and inference optimisation, and make pragmatic trade-offs on model size and performance - You communicate clearly and thoughtfully with colleagues across sites and cultures - You stay steady and keep your team moving when requirements are unclear or change often 🌱 Not ticking every box? That’s totally okay! If you’re passionate about autonomy and keen to learn, we encourage you to apply even if you don’t meet every requirement. More about Wayve: 🚗 Wayve is building the leading AI platform for autonomous driving. We are pioneering an end to end AI approach that enables vehicles to learn directly from real world experience, developing the ability to adapt, generalise and improve at scale. Instead of relying on hand coded rules or pre mapped environments, our AI Driver learns to drive by understanding the world around it. The result is technology that navigates complex urban environments with intelligence, precision and natural flow, unlocking meaningful advances in both safety and efficiency. We believe autonomy represents a once in a generation transformation in how people and goods move, comparable to the shift from horses to cars, and from human driven vehicles to intelligent machines. Our ambition is to make autonomy universal. Wayve’s mapless and hardware agnostic AI platform integrates with global OEM partners, enabling continuous software evolution and unlocking advanced levels of automation from L2 plus through to L4 as our core AI model scales. In a race increasingly defined by intelligence and real world learning, Wayve is taking a distinct approach, building a generalisable driving intelligence that can power any vehicle, anywhere. By combining embodied AI with scalable deployment, we are creating technology that can be shaped to each OEM brand and driver experience, accelerating the transition to a safer, more intelligent future of mobility. How we work 💻 — Locations & Flexible Working: Our main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. We operate a hybrid working model that combines in-person collaboration in our dedicated office spaces with focused time working remotely. This gives our teams the connection and energy of working together, alongside the flexibility to do their best work in a way that fits their lives. 📋 The Interview Process: ✏️ Recruiter: please update this section for the specific role before publishing. Our process is clear and respectful of your time: - Initial call / recruiter screen (30 mins) - Competency Interview (Technical Leadership & System Design; 2 hours) - Deep Dive (On-site visit in Herzilya; 1 hour) - Final interview: mission & values