Vice President of AI Data

Wayve; Sunnyvale (CA); On-site; USD 250,000 - 420,000; Full time

Benefits offered by this job

Private healthcare

Paid time off

Mental health resources

Community and socials

Competitive compensation

Learning and development

Job summary

Wayve in Sunnyvale, CA is hiring a VP of Data to lead the data strategy behind our autonomous driving technology and to own end-to-end data decisions that boost model performance.

You will build the data flywheel, determine which data matters, and lead a multidisciplinary Data organisation across Engineering, AI, Science, Validation, Product, Compute and Commercial teams.

Qualifications

• Senior technical leader at the intersection of AI, data and large-scale model development.
• Experience leading large-scale data capabilities that influence model training, evaluation and performance.
• Background in autonomous driving, robotics or embodied AI preferred.

Responsibilities

• Define Wayve's data strategy across the complete AI learning cycle to drive model performance.
• Lead the Data organisation and own data strategy within Engineering, partnering with AI, Science, Validation, Product, Compute and Commercial teams.
• Build and scale the data flywheel from real-world signals to training, evaluation, deployment and measurement.
• Discover rare, surprising, and safety-critical scenarios within large datasets using embeddings, semantic search and learned representations.
• Oversee data acquisition, enrichment, and trade-offs across quality, speed, cost, and scale.

Skills

Data strategy

AI leadership

Team leadership

Machine learning

Computer vision

Stakeholder mgmt

Job description

• We are looking for a VP of 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
• 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

Benefits

• Private healthcare: Choose our optional health insurance for comprehensive coverage for you and your family.
• Paid time off: Paid vacation plus public holidays and additional leave programs, ensuring you have time to unwind.
• Mental health resources: Through Spill, you can access therapy and mental health support.
• Community and socials: Join clubs or attend team socials to connect over hobbies, sports, or just for fun.
• Competitive compensation: Our compensation package includes cash and equity, making you a true partner in our success.
• Learning and development: Budgets for books, courses, and company-wide training to support your continuous growth.

You can hold the full system in your head while still going deep on the details that matterYou 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 operateYou 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 itYou are a senior technical leader who has operated at the intersection of AI, data and large-scale model developmentStrong technical and commercial judgement, including making trade-offs across quality, speed, cost, scale and build-versus-partner decisionsDeep technical expertise in computer vision, video, multimodal AI or related perception problemsSignificant engineering leadership experience, with a track record of building and leading high-performing technical organisationsExperience leading large-scale data capabilities that directly influence model training, evaluation and performanceStrong intuition for what makes data valuable, with experience in data discovery, selection, curation and enrichment at scaleAbility to move between strategy and technical detail, set direction in ambiguity, and influence effectively across senior technical and business stakeholdersAutonomous driving, robotics or embodied AISemantic search, embeddings, active learning, auto-labelling or other approaches to intelligent data selection and enrichmentLarge-scale real-world data acquisition across fleets, customers, partners or multiple geographiesLarge-scale video, multimodal or foundation model training