2 months ago
Germany (city not specified)Mid Level
Responsibilities
- Build and improve scalable data pipelines supporting autonomous-driving model development, evaluation, and production ML workflows.
- Ingest, transform, curate, and standardize large-scale real-world, synthetic, and partner-provided datasets.
- Develop data quality checks, validation processes, and monitoring for vehicle-platform and processed datasets.
- Curate and mine data to improve scenario diversity, coverage, and feature-specific development.
- Improve pipeline performance, reliability, usability, and iteration speed across ML development.
- Collaborate with ML engineers, Data Corpus, AI Platform, and external partners to integrate pipelines with production learning systems.
Requirements
- Proven experience building and operating scalable data pipelines or distributed data-processing systems in production.
- Strong Python software engineering skills and experience developing maintainable, reliable, and well-tested software.
- Proficiency in SQL and PySpark, including warehouse/OLAP concepts, window functions, and distributed Spark processing.
- Experience with modern data pipeline architectures and DAG-based workflow orchestration such as Airflow, Flyte, Ray, or similar.
- Understanding of robotics and automated-driving data concepts, including sensors, timestamping, clock synchronization, coordinate transformations, calibration, GNSS/IMU, and vehicle odometry.
- Understanding of machine learning workflows including training-data generation, evaluation datasets, scenario mining, and model iteration.
- Strong communication and collaboration skills for working with interdisciplinary teams.
- Experience in calibration, perception, imitation learning, trajectory prediction, or third-party dataset ingestion is desirable.
- Familiarity with automated-driving data and scenario taxonomies, including ODD definitions, maneuver and behavior labels, scene classification, event tagging, and semantic understanding, is desirable.
Benefits
- Full-time role based in the Leonberg office.
- Hybrid working policy combining office and workshop time with working from home.
- Core working hours with flexibility to determine a schedule that works for the employee and team.
- Inclusive interview experience with accommodations or adjustments available upon request.
Tech Stack
Categories
Data Engineering
About Wayve
Wayve builds end-to-end autonomous driving software—the vehicle-agnostic Wayve AI Driver—that runs on onboard compute and native sensors, licensed to automakers and fleet operators. Its platform spans ADAS and higher autonomy (L2+/L3 to robotaxi) and is designed to generalize across vehicle types and geographies. Founded in 2017 and headquartered in London, it tests its models across Europe, North America, and Japan, with a U.S. base in Sunnyvale, CA.