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Software Engineer; Data Platform

Remote / Online - Candidates ideally in
Greater London, London, Greater London, W1B, England, UK
Listing for: Wayve
Remote/Work from Home position
Listed on 2026-06-04
Job specializations:
  • Software Development
    Data Engineer, Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 80000 - 100000 GBP Yearly GBP 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Software Engineer (Data Platform)
Location: Greater London

Where you will have an impact

We’re looking for bold, talented and creative people to join our journey in developing next-generation autonomous vehicles. We’re a growing start-up, building our first cohort of engineers and you can be at the heart of this.

Data is key to our vision: our end-to-end machine learning approach is fundamentally data-driven. This makes this role an exciting opportunity to be at the heart of Wayve, with an opportunity to directly influence performance of self-driving algorithms.

We are looking for Software Engineers to help build the Wayve data platform which facilitates data ingestion, labelling, storage, curation and analysis of Wayve data.

Challenges you will own
  • The Data Platform team owns the data, infrastructure and tooling for the data we use to develop a learned driver.
  • You will be part of a growing group focussed on discovering the best data recipe for driving, exploring how far data can push autonomous driving performance.
  • You will be working across functions with machine learning research engineers, virtual world simulation engineers, robotics engineers and safety drivers to ingest, enrich and visualise thousands of hours of driving data.
  • You will have opportunities to develop new skills in data science, big data, analytics and data visualisation.
Examples Projects
  • Quality control and validation of datasets e.g. removing examples of bad driving.
  • Labelling, enrichment and augmentation of data at scale using thousands of GPUs simultaneously.
  • Orchestration of data processing and machine learning workloads by building out infrastructure for running Flyte and notebook environments (e.g. Google collab) at scale.
What you will bring to Wayve Essential
  • Proficiency in Python
  • Knowledge of software engineering practices - what makes code reusable and extensible.
  • Experience working closely with users, shaping data to fit their needs
  • Experience working with concurrent, parallel and distributed computing.
  • Passion for infrastructure: building internal tooling and frameworks.
  • Experience building reliable data pipelines to handle large data sets
  • Experience with cloud infrastructure, preferably Azure
  • Experience working with data processing technologies such as Databricks / Apache Spark, Apache Beam, Airflow or Flyte
Desirable
  • Experience with Docker, Kubernetes and Terraform
What we offer you
  • The chance to be part of a truly mission driven organisation and an opportunity to shape the future of autonomous driving. Unlike our competitors, Wayve is still relatively small and nimble, giving you the chance to make a huge impact
  • Competitive compensation and benefits
  • A dynamic and fast-paced work environment in which you will grow every day - learning on the job, from the brightest minds in our space, and with support for more formal learning opportunities too
  • A culture that is ego‑free, respectful and welcoming (of you and your dog) - we even eat lunch together every day
  • Benefits such as an onsite chef, workplace nursery scheme, private health insurance, cycle scheme, therapy, yoga, two onsite bars, large social budgets
  • This is a full‑time role based in our office in London. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. We also operate core working hours so you can be where you need to be for family and loved ones too.

    Teams determine the routines that work best for them.
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