Data Engineer for Autonomous Driving ML Pipelines

Wayve; United States; Hybrid; USD 89,000 - 140,000; Full time

Job summary

Wayve is hiring a Data Engineer to join the Machine Learning team in Application Software. You will design and deliver scalable data pipelines transforming vast data into model-ready datasets for autonomous driving.

You’ll collaborate with Data Corpus and ML engineers to build production-ready systems and drive high-quality data for model development. Essential experience in building production data pipelines, Python, SQL, PySpark, and modern orchestration tools is required.

Qualifications

• 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.

Responsibilities

• 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 standardised 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.

Skills

Python

SQL

PySpark

Data pipelines

ML workflows

Communication

Distributed systems

Tools

Airflow

Flyte

Ray

Job description

Wayve is hiring a Data Engineer to join the Machine Learning team in Application Software. You will design and deliver scalable data pipelines transforming vast data into model-ready datasets for autonomous driving.

You’ll collaborate with Data Corpus and ML engineers to build production-ready systems and drive high-quality data for model development. Essential experience in building production data pipelines, Python, SQL, PySpark, and modern orchestration tools is required.