# Lead Technical Program Manager, AI Platform

[Wayve](https://gurify.com/jobs?q=Wayve) · London, United Kingdom · Posted yesterday

Lead

[Project Manager](https://gurify.com/jobs/project-manager)

[AI & ML](https://gurify.com/jobs/ai-ml)

[Apply on the original posting → (opens in a new tab)](https://jobs.ashbyhq.com/wayve/002821a8-dd53-4737-be19-dc3270f4d39b)

## 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 PROGRAM MANAGEMENT TEAM

Wayve’s Program Management team turns complex technical goals into coordinated delivery. Working closely with engineering, research and product teams, we align priorities, manage dependencies and bring clarity to ambiguous challenges. We combine technical depth with cross-functional leadership to help teams move faster, more effectively and with purpose—focusing on meaningful outcomes rather than process for its own sake.

As part of this team, you’ll build and lead the technical programme management function supporting our AI Platform organisation. AI Platform builds the data and compute infrastructure, model-development workflow tooling, training technology, compute management, and embedded and inference optimisation that enable Wayve’s models to be trained, iterated and deployed onto the vehicle.

The systems this organisation delivers determine how quickly Wayve can develop and ship models, how efficiently we use compute, and how well our models perform in training and on the vehicle.

🧠 Your day-to-day

- Build, coach and support a small, high-impact TPM team, helping people develop their skills, work through challenges and raise the standard of programme delivery.

- Act as a trusted delivery partner to AI Platform and Engineering leadership, aligning priorities, challenging trade-offs and holding teams accountable for meaningful outcomes.

- Work across ML and research, infrastructure, embedded and on-vehicle engineering teams, as well as cloud and vendor partners, to manage dependencies, surface risks and remove blockers.

- Use KPIs, dashboards and operational reviews to understand delivery progress, identify bottlenecks and steer decisions with the right data.

- Represent AI Platform in company-level reviews, communicating progress, risks and decisions clearly while connecting delivery to business impact.

🧩 What you’ll be working on:

- Building and scaling the technical programme management function for AI Platform, hiring to fill capability gaps and growing a high-performing team.

- Owning planning, prioritisation and execution across the AI Platform roadmap in partnership with engineering leadership.

- Leading flagship programmes across data and compute infrastructure, developer tooling, training technology, compute management, model-development workflows, and embedded and inference optimisation.

- Establishing scalable planning cadences, governance, escalation paths and operational practices that bring structure without slowing delivery.

- Driving measurable improvements in developer velocity, compute efficiency and cost, training and inference performance, and platform reliability.

- Helping engineering leaders deliver high-leverage outcomes, balancing technical trade-offs and ensuring commitments translate into impact.

🙌 You should apply if:

- You bring 8+ years of hands-on technical programme management experience across platform, infrastructure, compute, ML infrastructure, developer tooling, training or inference systems. You have built or scaled a programme function, led people and processes, and get things done with ownership and a bias for action.

- You build, coach and grow high-performing teams. You know how to develop people, hire to strengthen the team and raise the bar on technical programme management.

- You have strong technical depth across ML infrastructure, compute and embedded systems. You can engage credibly with platform and systems engineers without being expected to write production code. Your experience includes:

 - A strong understanding of machine learning, GPUs, and training and inference for models from 500M to 20B+ parameters, including the compute and orchestration that support them.

 - Embedded or on-vehicle systems experience, including inference optimisation, deploying models to constrained edge compute, and hardware-software trade-offs.

 - Familiarity with compute management, ML platform tooling and model-development or experiment workflows, using technologies such as Kubernetes, Ray, Flyte, Docker, Azure and Python.

 - Proficiency with AI agents and coding assistants such as Cursor, Claude or Codex to accelerate execution.

- You stay objective under pressure and adapt your approach in ambiguous, fast-moving environments. You bring structure and clarity without creating unnecessary process or slowing delivery.

- You think in systems, understanding how the parts of a complex platform stack fit together and how changes in one area affect others.

- You’re product-minded, focusing on the people your programmes serve, prioritising by impact and defining what good looks like—not just tracking activity.

- You align and influence across ML and research, infrastructure, embedded and engineering teams without relying on formal authority.

- You connect technical investment to measurable outcomes, including developer velocity, compute efficiency, cost and model performance, and communicate direction and progress clearly using the right metrics.

- You’re open to feedback and continuously improve how you and your team work.

- Ideally, you have worked with a large-scale ML or compute platform used by hundreds of engineers and researchers.

- Experience with embedded or edge inference, on-device model optimisation, hardware-aware ML, autonomous vehicles, robotics or another large-scale ML and infrastructure environment would be valuable.

- An engineering or computer science degree, or experience working as an engineer, would be a plus.

🌱 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:

### Our process is clear and respectful of your time:

- Initial call / recruiter screen (30 minutes)

- Competency Interviews (TPM process, Cross-functional; 1 hour 45 minutes total)

- Deep-dive technical interviews (Program Design, Leadership & Management; 1 hour 45 minutes total)

- Final interview: mission & values alignment (30 minutes).

We’ll always explain the format and work around your availability.

### What’s in it for you (Location dependant):

💰 Salaries benchmarked against the market annually
📈 Meaningful equity, sharing in the ownership and long term success of Wayve
✈️ Relocation support and visa sponsorship where applicable
✅ Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs
📚 Learning and development budgets with support for training, conferences and growth
🩺 Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more

A quick, honest note before you apply.

Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you’ll help write it. That suits people who want real ownership more than people who need a settled structure from day one.

If that sounds like the kind of problem you want to spend your time on, we’d really like to hear from you.

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, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.

For more information visit Careers at Wayve. https://wayve.ai/careers/ To learn more about what drives us, visit Values at Wayve https://wayve.ai/careers/

DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.

**Live in Wayve’s hiring system.** Read from the company's own applicant tracking system, not reposted from a job board — so it's a real, open requisition rather than an ad that outlived the role.

We remove it as soon as it disappears at source.

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You bring structure and clarity without creating unnecessary process or slowing delivery.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EYou think in systems, understanding how the parts of a complex platform stack fit together and how changes in one area affect others.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EYou\u2019re product-minded, focusing on the people your programmes serve, prioritising by impact and defining what good looks like\u2014not just tracking activity.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EYou align and influence across ML and research, infrastructure, embedded and engineering teams without relying on formal authority.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EYou connect technical investment to measurable outcomes, including developer velocity, compute efficiency, cost and model performance, and communicate direction and progress clearly using the right metrics.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EYou\u2019re open to feedback and continuously improve how you and your team work.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EIdeally, you have worked with a large-scale ML or compute platform used by hundreds of engineers and researchers.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EExperience with embedded or edge inference, on-device model optimisation, hardware-aware ML, autonomous vehicles, robotics or another large-scale ML and infrastructure environment would be valuable.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EAn engineering or computer science degree, or experience working as an engineer, would be a plus.\u003C/li\u003E\u003C/ul\u003E\u003Cp\u003E\u0026#127793; Not ticking every box? 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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.\u003C/p\u003E\u003Cp\u003EOur ambition is to make autonomy universal. Wayve\u2019s 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.\u003C/p\u003E\u003Ch3\u003EHow we work \u0026#128187;- Locations \u0026amp; Flexible Working:\u003C/h3\u003E\u003Cp\u003EOur 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. 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