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About the Role

We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Every role here, whatever the team, plugs into that.

Responsibilities

Design and deliver scalable data pipelines that turn vast amounts of data from diverse internal and external sources into structured, reliable and model-ready datasets.
Work spans data ingestion, data quality assurance, transformation, curation, evaluation and ML support.
Work closely with Wayve’s Data Corpus teams, customer programmes and ML engineers, bringing up ingestion pipelines for new vehicle platforms and sensor configurations, and tackling the highest-impact bottlenecks first.
Building and improving scalable data pipelines that support model development, evaluation and production ML workflows for autonomous driving.
Ingesting, transforming and curating large-scale real-world, synthetic and partner-provided datasets into structured, reliable, model-ready formats aligned with standardised taxonomies and coordinate systems.
Developing data quality checks, validation processes and monitoring so that raw vehicle data and processed datasets are high-quality, complete, consistent, traceable and fit for ML use cases.
Curating and mining real-world and synthetic data to drive scenario diversity, coverage and feature-specific development.
Improving pipeline performance, reliability and usability, reducing bottlenecks and increasing iteration velocity across ML development.
Collaborating closely with ML engineers, Data Corpus, AI Platform and external partners so data pipelines integrate effectively with production-scale learning systems.

Requirements

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.
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, manoeuvre and behavior labels, scene classification, event tagging, semantic understanding.

Skills

Python
SQL
PySpark
Airflow
Flyte
Ray

Location

London
Sunnyvale
Yokohama
Herzliya
Vancouver
Leonberg

Work Type

Hybrid working

Salary/Compensations

Salaries benchmarked against the market annually

Benefits

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

About the Company

Wayve is building the leading AI platform for autonomous driving.
We are pioneering an end to end AI approach that enables vehicles to learn directly from real world experience, developing the ability to adapt, generalise and improve at scale.
Instead of relying on hand coded rules or pre mapped environments, our AI Driver learns to drive by understanding the world around it.
The result is technology that navigates complex urban environments with intelligence, precision and natural flow, unlocking meaningful advances in both safety and efficiency.
We believe autonomy represents a once in a generation transformation in how people and goods move, comparable to the shift from horses to cars, and from human driven vehicles to intelligent machines.
Our ambition is to make autonomy universal.
Wayve’s mapless and hardware agnostic AI platform integrates with global OEM partners, enabling continuous software evolution and unlocking advanced levels of automation from L2 plus through to L4 as our core AI model scales.
In a race increasingly defined by intelligence and real world learning, Wayve is taking a distinct approach, building a generalisable driving intelligence that can power any vehicle, anywhere.
By combining embodied AI with scalable deployment, we are creating technology that can be shaped to each OEM brand and driver experience, accelerating the transition to a safer, more intelligent future of mobility.

Equal Opportunity

At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.
For more information visit Careers at Wayve.
To learn more about what drives us, visit Values at Wayve
DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews.
However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.