Description
We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future.
We're seeking an exceptional Data Engineer to join our Germany-based team within the Application Engineering org, focused on localising and advancing Wayve's autonomous driving technology for the German market.
Your day-to-day
- Build and improve scalable data pipelines that support model development, evaluation, and production ML workflows for autonomous driving.
- Ingest, transform, and curate large-scale real-world, synthetic, and partner-provided datasets into structured, reliable, and model-ready formats aligned with standardized taxonomies and coordinate systems.
- Develop data quality checks, validation processes, and monitoring to ensure both raw data from our vehicle platforms and processed datasets are high-quality, complete, consistent, traceable, and fit for ML use cases.
- Curate and mine real-world and synthetic data to drive scenario diversity, coverage, and feature-specific development.
- Improve pipeline performance, reliability, and usability, helping reduce bottlenecks and increase iteration velocity across ML development.
- Collaborate closely with Machine Learning engineers, Data Corpus, AI Platform, and external partners to ensure data pipelines integrate effectively with production-scale learning systems.
What you'll be working on As a Data Engineer within the Machine Learning team in Application Software, you'll contribute to critical initiatives that push the frontier of model-based autonomous driving,both in terms of core driving performance and feature-level intelligence such as personalization, comfort, and collaboration.
Essential skills
- Proven experience building and operating scalable data pipelines or distributed data processing systems in production environments.
- Strong software engineering skills in Python, with a solid foundation in maintainable, reliable, and well-tested software development practices.
- Proficient in SQL and PySpark, with experience using warehouse/OLAP concepts, window functions, and Spark for distributed data processing.
- Experience with modern data pipeline architectures, including workflow orchestration and DAG-based systems such as Airflow, Flyte, Ray, or similar.
- Solid understanding of robotics and automated driving data concepts, including sensor characteristics, timestamping and clock synchronisation, coordinate transformations, calibration, and ego-motion signals such as GNSS/IMU and vehicle odometry.
- Understanding of machine learning development workflows, including training data generation, evaluation datasets, scenario mining, and model iteration.
- Excellent communication and collaborative skills, capable of working effectively with interdisciplinary teams.
Desirable skills
- Prior work in calibration, perception, imitation learning, or trajectory prediction.
- Experience with third-party dataset ingestion and transformation.
- Familiarity with automated driving data and scenario taxonomies, including ODD definitions, maneuver and behavior labels, scene classification, event tagging, semantic understanding.
Benefits
- Salaries benchmarked against the market annually
- Meaningful equity, sharing in the ownership and long term success of Wayve
- Relocation support and visa sponsorship where applicable
- Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs
- Learning and development budgets with support for training, conferences and growth
- Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more