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Wayve is building an AI platform for autonomous driving that enables vehicles to learn from real-world experience. The Data Quality & Provenance team sits within the AI Platform organisation and builds the trusted data foundations behind Wayve's self-driving technology, operating at petabyte scale.
In this role, you will design and operate scalable batch and streaming pipelines for multimodal fleet and simulation data. You'll build data models, catalogues, indexes and query capabilities that make sensor, vehicle-state, map and event data discoverable and usable. Your work will create versioned, reproducible datasets for training, evaluation, replay, scenario mining and safety analysis.
Day-to-day responsibilities include:
- Designing and operating scalable batch and streaming pipelines for multimodal fleet and simulation data
- Building data models, catalogues, indexes and query capabilities for sensor, vehicle-state, map and event data
- Creating versioned, reproducible datasets for training, evaluation, replay, scenario mining and safety analysis
- Developing workflows for data ingestion, synchronisation, transformation, curation, labelling and quality validation
- Partnering with autonomy, ML, simulation and safety engineers to define schemas, APIs and data contracts
- Improving reliability, performance and cost efficiency of large-scale storage and compute workloads
You'll work on petabyte-scale data products supporting autonomous-driving development, trusted datasets with strong versioning and lineage guarantees, metadata and geospatial indexing for data discovery, systems combining real-world fleet logs with simulation and synthetic data, data-quality standards and observability, and cloud-based storage and distributed-compute infrastructure.
Wayve operates a hybrid working model with main hubs in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. The company offers competitive salaries benchmarked against the market, meaningful equity, relocation support and visa sponsorship where applicable, learning and development budgets, and comprehensive benefits including health insurance, dental, enhanced parental leave, retirement/pension, access to therapists and wellbeing partnerships.
REQUIREMENTS:
- Strong hands-on Python and SQL skills with solid production software-engineering fundamentals
- Experience designing and operating large-scale distributed data systems beyond small analytics or reporting pipelines
- Production experience with distributed-processing and workflow-orchestration technologies such as Spark, Flyte or Airflow
- Experience building cloud-based data platforms using object storage, with understanding of data organisation, versioning, querying, governance and cost management
- Ownership of data quality, lineage, observability, reproducibility and incident response for production data workflows
- Ability to translate ambiguous requirements from ML, data-science, robotics or similarly technical teams into durable, reusable platform capabilities
- Comfort working in ambiguity and helping define standards and operating models for a growing data platform
- Advantageous: experience with autonomous vehicles, ADAS, robotics, mapping, sensor-rich systems, geospatial data or multimodal datasets
