Vice President, AI Data

Wayve

London (KY)

Hybrid

USD 190,000 - 260,000

Full time

14 days+
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Job summary

Wayve is seeking a VP of AI Data to own the data strategy behind its autonomous driving AI. You will set the data needs, shape acquisition and enrichment, and drive measurable model performance improvements.

This senior leadership role requires building a global Data organisation and partnering across AI, Science, Validation, Product, Compute and Commercial teams. You will lead data acquisition across our fleet, OEM programmes, partners and external sources, balancing coverage, quality, speed

Qualifications

  • Significant engineering leadership experience.
  • Deep technical expertise in computer vision, video, multimodal AI or related perception problems.
  • Experience leading large-scale data capabilities that influence model training, evaluation and performance.
  • Strong intuition for what makes data valuable, with experience in data discovery, selection, curation and enrichment at scale.
  • Strong technical and commercial judgement, including trade-offs across quality, speed, cost, scale.

Responsibilities

  • Own Wayve's data strategy across the AI learning cycle from data needs to production impact.
  • Build the data flywheel from real-world signals through to training, evaluation and measurement.
  • Find data that matters via rare, surprising, safety-critical scenarios in large datasets.
  • Lead data acquisition and enrichment across our fleet, OEMs, partners and external sources.
  • Connect data investment to model performance with rigorous trade-offs on quality, speed, cost and scale.
  • Scale the data strategy globally across geographies, vehicle platforms and regulations.
  • Build and lead a high-performing, multidisciplinary Data organisation in partnership with AI, Science, Validation, Product, Compute and Commercial teams.

Skills

Engineering leadership
CV/Multimodal AI
Large-scale data
Data discovery & enrichment
Technical & commercial judgement
Strategy-to-implementation

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.

The role

At Wayve, we are building AI that learns to drive from experience.

We do not hand-code cars to drive. We train our models from data gathered across the real world, making our ability to identify, understand and learn from the right data fundamental to everything we build.

We are looking for a VP of AI Data to lead the data strategy behind our autonomous driving technology.

This is a senior engineering leadership role with end-to-end ownership of how Wayve uses data to improve our AI. You will determine what data we need, how we acquire it, how we understand and enrich it, and ultimately how we turn it into measurable improvements in model performance.

The scale and shape of the problem is unique. Our data comes from our own vehicles, OEM programmes, partners and external sources, spanning different vehicles, sensors, markets and driving environments. Within that corpus, the most valuable examples are often the hardest to find: rare behaviours, unusual interactions, safety-critical events and the long tail of real-world driving.

Your job is not simply to build the systems that process this data. It is to decide what data matters and why, and build the strategy, organisation and learning loop that allows Wayve to learn from it faster.

You will lead Wayve's Data organisation and provide senior ownership for data within Engineering, partnering closely across AI, Science, Validation, Product, Compute and our commercial teams.

Key Responsibilities

  • Own Wayve's data strategy: Set the strategy across the complete AI learning cycle, determining what data we need and how it should drive model performance, from foundation model training through specialised driving capabilities and production programmes.

  • Build the data flywheel: Own the learning loop from real-world signals and model behaviour through data discovery, curation and enrichment into training, evaluation, deployment and measurement.

  • Find the data that matters: Develop intelligent approaches to discovering rare, surprising and safety-critical scenarios within extremely large datasets, using techniques such as embeddings, semantic search, learned representations and model-driven data selection.

  • Lead data acquisition and enrichment: Define how Wayve collects, buys, generates and enriches data across our own fleet, OEM programmes, partners and external sources, balancing coverage, quality, speed and economics.

  • Connect data investment to model performance: Establish how we measure the value of data and make rigorous trade-offs across quality, accuracy, speed, cost and scale, ensuring investment is focused where it creates the greatest impact.

  • Scale our data strategy globally: Build an approach that supports multiple OEMs, vehicle platforms, sensor configurations, geographies and regulatory environments while maintaining a scalable global architecture.

  • Build and lead the organisation: Lead and develop a high-performing, multidisciplinary Data organisation, partnering closely with AI, Science, Validation, Product, Compute, Finance and Commercial teams.

About You

You are a senior technical leader who has operated at the intersection of AI, data and large-scale model development.

You can set direction in ambiguity and make high-quality decisions without perfect information. You are equally comfortable going deep into the characteristics and value of a dataset, challenging how a team measures model improvement, making significant investment decisions, or defining how an organisation should operate.

You have strong technical judgement, but think about data through the impact it has on the intelligence and performance of the system, rather than simply the infrastructure required to store and process it.

You can hold the full system in your head while still going deep on the details that matter.

Essential

  • Significant engineering leadership experience, with a track record of building and leading high-performing technical organisations.

  • Deep technical expertise in computer vision, video, multimodal AI or related perception problems.

  • Experience leading large-scale data capabilities that directly influence model training, evaluation and performance.

  • Strong intuition for what makes data valuable, with experience in data discovery, selection, curation and enrichment at scale.

  • Strong technical and commercial judgement, including making trade-offs across quality, speed, cost, scale and build-versus-partner decisions.

  • Ability to move between strategy and technical detail, set direction in ambiguity, and influence effectively across senior technical and business stakeholders.

Desirable

Experience in one or more of the following areas would be a strong advantage:

  • Autonomous driving, robotics or embodied AI.

  • Large-scale video, multimodal or foundation model training.

  • Semantic search, embeddings, active learning, auto-labelling or other approaches to intelligent data selection and enrichment.

  • Large-scale real-world data acquisition across fleets, customers, partners or multiple geographies.

This is a full-time role based in either our in Sunnyvale or London office. At Wayve we want the best of all worlds, so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.

LA1

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.

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