Data Engineer Application Software
Wayve is a London-headquartered embodied-AI company developing and licensing mapless, vehicle-agnostic driving software for assisted, automated, and robotaxi applications.
About Wayve
Wayve Technologies Ltd. develops the Wayve AI Driver, an end-to-end, data-trained software platform that runs on onboard vehicle compute and native sensors. It is designed for OEM integration across L1 driver assistance through L4 automated driving, without HD maps.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will build and improve scalable data pipelines for model development, evaluation, and production machine-learning workflows. You will ingest, transform, curate, validate, and monitor large-scale datasets, improve pipeline performance and reliability, and work with engineering and external partners to integrate data systems with production learning platforms.
Requirements
- Experience building and operating scalable data pipelines or distributed data-processing systems in production
- Python software engineering
- SQL
- PySpark
- Warehouse and OLAP concepts
- Spark distributed data processing
- Workflow orchestration and DAG-based systems such as Airflow, Flyte, or Ray
- Robotics and automated-driving data concepts
- Sensor characteristics, timestamping, clock synchronisation, coordinate transformations, calibration, GNSS, IMU, and vehicle odometry
- Machine-learning development workflows
- Communication and collaboration skills
Responsibilities
- Build and improve scalable data pipelines for autonomous-driving machine-learning workflows
- Ingest, transform, and curate real-world, synthetic, and partner datasets
- Develop data-quality checks, validation processes, and monitoring
- Curate and mine data to improve scenario diversity and coverage
- Improve pipeline performance, reliability, and usability
- Collaborate with machine-learning engineers, data teams, platform teams, and external partners
Benefits
- Hybrid working
- Core working hours with flexible scheduling