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Oxa

Autonomous driving software for multi-vehicle platforms

Technical Program Manager - Data

Program ManagementPosted on Nov 12
Full-timeOxford, UK

About the Job

Requirements

  • A career that started in engineering, with a degree in computer science, software, data, electrical, robotics or a similar field, and moved into delivery, with at least 2 years as a Technical Program Manager, project engineer or delivery manager on a technical product.
  • Knowledge of the data and machine-learning lifecycle, including how data moves from collection through curation, labelling and dataset release to model training and evaluation, and why data quality and versioning matter.
  • Enough data and cloud fluency to follow engineering discussions and ask good questions about data pipelines, cloud storage and compute, datasets, labelling, and simulation.
  • Ability to break down work, map dependencies and forecast from data using tools such as Jira, Confluence and Miro, and build trust with engineers when priorities shift.

Responsibilities

  • Take the layer's commitments in the product engineering plan and, with the leads, turn them into sequenced work with dates and a clear definition of done.
  • Bring the teams' planning into Jira with little overhead and keep work traceable to the products it supports.
  • Run regular triage of data-quality issues affecting model training, such as calibration, timing and labelling problems, ensuring every issue has an owner, priority and next step.
  • Coordinate the data, scenarios and simulation each new operating site needs so they are ready when the site goes live.
  • Run the layer's cloud cost reporting and help leads balance cost against keeping needed data available.
  • Track dependencies between the teams and others, raise conflicts early and broker trade-offs involving vehicle and ingest-pipeline data, datasets, scenarios and simulation for model training and testing, and external labelling and cloud compute providers.
  • Report monthly progress against plan, data-quality health and cost health, using metrics such as dataset turnaround time and cost per training cycle to show whether delivery is improving.
  • Identify sources of friction, such as manual curation steps, unclear ownership or slow data turnaround, and drive fixes with the teams.

Desired Qualifications

  • Hands-on experience in data engineering, machine learning or simulation.
  • Experience in automotive, robotics or other autonomous systems.
  • Experience with MLOps, data platforms or labelling operations.
  • Exposure to simulation, synthetic data generation or digital twins.
  • Experience tracking or optimising cloud spend.
  • Comfort with Git-based planning, documentation-as-code or AI tools for reporting.

About the Company

Oxa

Autonomous driving software for multi-vehicle platforms

Oxa provides a universal autonomy software platform that enables autonomous driving across passenger shuttles, logistics vehicles, and industrial machinery for commercial and industrial use. The platform runs onboard perception, planning and control and pairs with cloud-based fleet management, analytics, and simulation tools to train and validate systems, including GPS-denied operation in complex environments. It differentiates itself by targeting near-term, revenue-generating deployments with a single adaptable stack for multiple vehicle types and by leveraging its Oxford University research origins to create deployable autonomy solutions. Its goal is to deliver safe, scalable autonomy for mobility and industrial automation in real-world sites.

Company size
201-500
Company stage
Series D
Total funding
$354.5M
Headquarters
Oxford, United Kingdom
Founded
2014

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