ADAS Feature Engineer, Application Software

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 Engineering Teams🛠️
AI Platform builds the platform the whole company builds on: the data and compute infrastructure,
model-development workflow tooling, training technology, compute management, and embedded /
inference optimisation that get Wayve’s models trained, iterated and deployed onto the vehicle.
The systems this team delivers determine how fast 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🧠
As the Lead Technical Program Manager for AI Platform, you’ll build and lead the technical
program management function for the organisation. You’ll be the delivery partner to engineering
leadership, driving predictable, high-leverage delivery across the platform roadmap.
You’ll lead flagship programs directly while supporting and coaching a small, high-impact TPM
team. Your impact will be measured in developer velocity, compute efficiency and cost, training
and inference performance, and the reliability of platform delivery. A successful TPM leader is a
force multiplier—helping teams move faster, more effectively and with purpose.
What you’ll be working on:🧩
• Building and leading the function: Build, coach and grow a small TPM team, hiring to fill
gaps and raising the bar for technical program management.
• Owning platform delivery: Partner with AI Platform leadership on planning, prioritisation and
execution across data and compute infrastructure, developer tooling, training technology,
compute management, and embedded / inference optimisation.
• Being a trusted partner to engineering leadership: Operate as a leader within the
organisation, helping engineering leaders deliver high-leverage outcomes and holding them
accountable for commitments and impact.
• Driving flagship programs directly: Lead complex programs across the platform stack, from
infrastructure and model-development workflows to training systems and on-vehicle inference.

2
• Establishing scalable practices: Develop planning cadences, governance, KPIs,
dashboards, escalation mechanisms and operational reviews that bring structure without
slowing delivery.
• Aligning teams and partners: Work across ML / research, infrastructure, embedded / on-
vehicle and engineering teams, alongside cloud and vendor partners, to manage
dependencies, risks and trade-offs.
• Connecting delivery to outcomes: Tie platform delivery to developer velocity, compute
efficiency and cost, and training / inference performance, representing AI Platform in company-
level reviews.
You should apply if:🙌
Essential
• You bring 8+ years of platform / infrastructure program experience. You’ve delivered
complex programs across compute, ML infrastructure, developer tooling, training or inference
systems, including people and process leadership. You’ve built or scaled a program function
and bring ownership and a bias for action.
• You build strong teams. You have experience building, coaching and growing high-
performing teams, raising the bar for the craft of technical program management.
• You’re a genuinely technical TPM. You can go deep with platform and systems engineers
across ML infrastructure, compute and embedded systems, even though you won’t write
production code. This includes:
• A strong understanding of machine learning, GPUs, and the training and inference of large
models—from 500M to 20B+ parameters—including the compute and orchestration that
support them.
• Embedded / 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 /
experiment workflows, using technologies such as Kubernetes, Ray, Flyte, Docker, Azure
and Python.
• Proficiency with AI agents and coding assistants, such as Cursor, Claude and Codex, to
accelerate execution.
• You stay neutral and adapt under pressure. You’re effective in ambiguous, fast-moving
environments, flexing your style and bringing structure without slowing teams down.
• You think in systems. You understand how the parts of a complex platform stack fit together
and how changes in one area affect others.
• You’re product-minded. You prioritise by impact, focus on the people your programs serve,
and define what good looks like rather than simply tracking activity.
• You lead across functions. You align and influence ML / research, infrastructure, embedded
and engineering teams without relying on authority.

3
• You connect technical investment to business impact. You link platform decisions to
measurable improvements in developer velocity, compute efficiency, cost and model
performance.
• You communicate clearly and use data well. You set direction with clarity and steer delivery
using the right metrics.
• You bring a growth mindset. You’re open to feedback and always looking to improve.
Desirable
• Experience with a large-scale ML / compute platform used by hundreds of engineers and
researchers.
• Embedded / edge inference, on-device model optimisation or hardware-aware ML experience.
• A background in autonomous vehicles, robotics or another large-scale ML / infrastructure
program.
• An engineering or computer science degree, or experience working as an engineer.
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 mins)

• Competency Interviews (C++ programming; 1 hours total)

• Deep-dive technical interviews (ADAS / AD domain knowledge, system design and, technical leadership; 2-3 hours total)

• Final interview: mission & values alignment (1 hour).

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. 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 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.