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Wayve is building the leading AI platform for autonomous driving, pioneering an end-to-end AI approach that enables vehicles to learn directly from real-world experience. The Map & Route team sits within Wayve's Automotive Platforms division in Vehicle Software Engineering and builds the geospatial foundations behind the AI driver.
In this role, you will work on global-scale geospatial data, turning road-network and navigation data into reliable products used across Wayve. The team is full-stack, owning mapping end-to-end with work spanning infrastructure, data engineering, data science, backend, and frontend.
Day-to-day responsibilities include:
- Writing full-stack services in Python and TypeScript to create novel geospatial services solving unique problems in building AI driving products
- Collaborating with internal teams to understand requirements and build solutions with global geospatial data
- Designing and building data pipelines with PySpark and Databricks to enrich fleet data with mapping and road-network information at global scale
- Building applications and datasets that support route planning and map data preparation for training and simulation
- Integrating with navigation and mapping APIs from providers such as Mapbox, TomTom, and Google Maps
- Maintaining, supporting, and improving existing team services
- Deploying and operating services on Azure and Kubernetes, owning them end-to-end
Key projects include global-scale geospatial enrichment pipelines, route-planning applications and datasets, map data preparation for model training and simulation, and new services taken from idea to production.
Wayve operates a hybrid working model with main hubs in London, Sunnyvale, Yokohama, Herzliya, Vancouver, and Leonberg, combining in-person collaboration with focused remote work time.
REQUIREMENTS:
- Strong, hands-on Python engineer capable of delivering high-quality production code at pace
- Comfortable with AI-assisted or AI engineering workflow (ideation, planning, implementation, review)
- Experience building and operating large-scale data pipelines using Spark or PySpark
- Proficiency writing SQL to query and analyze large datasets
- Working knowledge of cloud infrastructure and container orchestration, ideally Azure and Kubernetes, with willingness to own deployment, monitoring, and observability
- Enjoys taking ownership of new services and seeing them through end-to-end
- Strong advantage: experience with geospatial data processing, road-network data, or routing engines (e.g., OpenStreetMap, TomTom, HERE, Overture data, PostGIS, navigation APIs)
- Desirable: experience with Bazel or monorepo build systems
- Bonus: experience with workflow orchestration tools such as Flyte or Airflow
Note: The posting encourages applications even if you don't meet every requirement, particularly if passionate about autonomy and keen to learn.
