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OxaOX

Data Engineer - ML Systems for Autonomous Driving

Oxa is an autonomous vehicle software company that develops software to enable any vehicle to be self-driving, anywhere, at any time. Their solutions are designed for various industries, aiming to make transportation safer, more efficient, and sustainable.

Oxa

Employee count: 201-500

United States only

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Who are we?

Founded in 2014, Oxa is a global leader in autonomous vehicle (AV) technology, dedicated to accelerating Industrial Mobile Autonomy (IMA). We develop advanced physical AI and robotics technology, anchored around our configurable and explainable self-driving software, Oxa Driver; development toolchain, Oxa Foundry; and fleet management software, Oxa Hub. We utilise hardware blueprints known as Reference Autonomy Designs (RADs) to enable the integration of sensors, compute and drive-by-wire systems into existing vehicles produced by OEMs. Our solutions automate repetitive industrial driving tasks, such as the towing and carrying of goods in locations like ports, airports and manufacturing facilities, or asset and perimeter monitoring in environments such as solar farms or industrial plants. We’re helping global businesses to address critical challenges like labour shortages and rising operational costs - driving efficiency, productivity, and safety. Based in Oxford, and with offices in Canada, our engineering team is drawn from the world’s top physical AI specialists and led by originators of the field.

Your Role:

We are hiring a Data Engineer to help build the systems that prepare, curate, and scale training and evaluation data for machine learning in autonomous driving. You will work across the full data lifecycle, from raw vehicle logs and simulation outputs to curated, labelled, and model-ready datasets. This includes handling multimodal sensor data, scaling labelling through both human and ML-based workflows, and enabling intelligent selection of high-value data from thousands of hours of real-world and simulated driving. This role sits close to model performance and safety ensuring quality, structure, and selection of data directly influence how perception and planning systems behave in the real world.

What You Will Work On:

You will work on systems that:

  • Transform raw multimodal logs (camera, LiDAR, radar) into training-ready datasets
  • Support hand-labelled and auto-labelled data pipelines, including validation and quality control
  • Help build and scale autolabelling systems, where ML models generate annotations across large datasets
  • Support intelligent data curation and selection from thousands of hours of real-world and simulated driving
  • Generate and process simulated data for perception and planning, ensuring sufficient sim-to-real fidelity for synthetic data to be useful in training and evaluation
  • Manage multiple data representations, including sensor-native formats (images, point clouds), structured scene representations (objects, semantics, occupancy), and bird’s-eye view (BEV) representations for downstream models
  • Support dataset generation for perception models (for example detection, segmentation, and occupancy) and planning models (behavioural learning)

Key Responsibilities:

  • Design, build, and maintain scalable data pipelines from raw logs to training datasets
  • Contribute to systems for dataset generation, versioning, and reproducibility
  • Develop and operate autolabelling pipelines, integrating model outputs into labelling workflows
  • Implement quality control mechanisms for both human and ML-generated labels
  • Support ML-assisted data curation workflows to identify high-value or failure-prone scenarios
  • Build pipelines to generate, transform, and validate simulated datasets, helping identify and reduce sim-to-real mismatches to improve their usefulness for training and evaluation
  • Work closely with ML engineers to translate model requirements into data pipelines and datasets
  • Debug data issues across the stack, from sensor-level artefacts to dataset inconsistencies
  • Improve storage, compute, and throughput efficiency for large-scale datasets

What You Need to Succeed:

  • Strong software engineering skills, with Python as a primary language
  • Strong SQL skills and experience working with analytical data warehouses (e.g. BigQuery, Snowflake)
  • Experience building production-grade data pipelines or distributed data systems
  • Experience working with large-scale datasets
  • Familiarity with cloud infrastructure (e.g. GCP, AWS, or similar)
  • Solid understanding of data modelling, transformation, and data quality considerations

Extra Kudos If You Have:

  • Experience working with ML data pipelines or supporting ML systems
  • Familiarity with computer vision, robotics, or autonomous systems
  • Experience working with multimodal sensor data, such as images, LiDAR, or radar
  • Exposure to labelling workflows, autolabelling, or dataset curation
  • Experience with spatial or geospatial data
  • Familiarity with Linux-based development environments
  • Experience with tools such as Docker, shell scripting, workflow orchestrators, and transformation frameworks (e.g. Hera Workflows, dbt)

Benefits:

  • Competitive salary, benchmarked against the market and reviewed annually
  • Company share programme
  • Hybrid and/or flexible remote working arrangements
  • Core benefits of market leading private healthcare, life assurance, critical illness cover, income protection, alongside a company paid health cash plan (including gym discounts)
  • A salary exchange pension plan
  • 25 days’ annual leave plus bank holidays
  • A pet-friendly office environment
  • Safe assigned spaces for team members with individual and diverse needs

Our Culture:

We are on a mission to unlock the benefits of self-driving technology to every person and organisation on the planet. We are creating an environment where everyone, from any background, can do their best work which, put simply, is the right thing to do. We hire and nurture those we can learn from, valuing diversity and the innovation that this drives. We promote an open and inclusive culture that empowers our Oxbots to bring their whole, authentic selves to work every day.

Why become an Oxbot?

Our team of experts in computer science, AI, robotics and machine learning is world-class, and together they’re solving the most exciting and important technological challenges of our times. Our diverse, multi-cultural crew is guided by a shared vision to bring the myriad benefits of autonomy to our customers and partners. And in a company that celebrates uniqueness as much as skill and experience, we do it with energy, conviction and a healthy dose of excitement, too. If you are bold, creative and hyper skilled, come and create the future of autonomy with us at Oxa.

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About Oxa

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We are Oxa, and we're on a mission to change the way the Earth moves. Founded in 2014 by Oxford professors Paul Newman and Ingmar Posner, we began with a singular vision: to build software that enables any vehicle to be self-driving, anywhere, at any time. We call this Universal Autonomy™. Over the past decade, our team has grown to over 400 passionate individuals, all dedicated to accelerating the transition to self-driving technology. Our software solutions empower businesses to deploy autonomy into their operations safely, securely, and efficiently. From passenger shuttles and goods delivery to complex industrial environments like mines and refineries, our technology is designed to be versatile and adaptable.

At Oxa, we develop a full stack, end-to-end Universal Autonomy software platform that is vehicle and platform-agnostic, meaning it doesn't rely on external infrastructure like GPS. This allows our software to be deployed in any environment and on any terrain, including challenging locations such as underground, in natural canyons, forests, and even 'urban canyons' where GPS signals are weak. Our product suite includes Oxa Driver, a comprehensive autonomy system; Oxa Hub, which connects autonomous vehicles to fleet and data management platforms; and Oxa MetaDriver, a suite of tools leveraging generative AI and digital twins for machine learning and testing. We are proud of our history of world firsts, including the first commercial deployment of Oxa Driver in partnership with Beep in 2024 and being the first and only autonomy company to have its safety case successfully assessed by BSI in 2021. We collaborate with key players across the industry, including Google Cloud, Nvidia, bp, and Ocado Technology, to bring the benefits of autonomy to a wide range of applications. Our commitment is to unlock the benefits of self-driving technology for every person and organization on the planet, creating a safer, cleaner, and more sustainable future.

Employee benefits

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Visa programme

Visa programme.

Relocation support

Relocation support.

Cycle to Work scheme

Cycle to Work scheme.

Employee resource groups

Employee resource groups.

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