Vice President, AI Data

Wayve builds AI that learns to drive from experience rather than hand-coded rules. The VP of Data will lead the Data organisation, which determines what data Wayve needs, how it is acquired and understood, and how it is turned into measurable improvements in its AI Driver. The role can be based in either the London or Sunnyvale office.

Responsibilities

Own Wayve's data strategy across the complete AI learning cycle; Build the data flywheel by owning 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 by discovering rare, surprising and safety-critical scenarios within extremely large datasets; Lead data acquisition and enrichment across own fleet, OEM programmes, partners and external sources; Connect data investment to model performance by measuring the value of data and making trade-offs across quality, accuracy, speed, cost and scale; Scale the data strategy globally across multiple OEMs, vehicle platforms, sensor configurations, geographies and regulatory environments; Build and lead a high-performing, multidisciplinary Data organisation

Requirements

Senior engineering or technical leader with significant experience building and leading high-performing technical organisations; Experience operating at the intersection of AI, data and large-scale model development, with data capabilities that directly influence model training, evaluation and performance; Deep technical expertise in areas such as computer vision, video, multimodal AI, perception or related large-scale ML problems; Strong intuition for what makes data valuable, with experience in data discovery, selection, curation and enrichment at scale; Ability to move between strategy and technical detail, from organisation-wide data strategy to going deep on a dataset, model behaviour or learning loop; Strong technical and commercial judgement, with meaningful trade-offs across quality, speed, cost, scale and build-versus-partner decisions; Comfortable setting direction in ambiguity and influencing senior technical and business stakeholders across organisational boundaries

Nice to have

Experience in autonomous driving, robotics or embodied AI; Experience with large-scale video or multimodal foundation model training; Experience with semantic search, embeddings, active learning, auto-labelling, or large-scale real-world data acquisition

Benefits

Salaries benchmarked against the market annually; Meaningful equity; Relocation support and visa sponsorship where applicable; Hybrid working, core hours and opportunity to work closely with vehicles, workshops and labs; Learning and development support, including training, conferences and growth opportunities; Comprehensive location-dependent benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension support, access to therapists, wellbeing partnerships and team socials