Description

Who are we?

Oxa is enabling the transition to self-driving vehicles through an initial focus on the most commercially advanced sector; the autonomous shuttling of goods and people.

We are home to some of the world’s leading experts on autonomous vehicles, creating solutions such as Oxa Driver, equipping vehicles with full self-driving functionality; Oxa MetaDriver, using Generative AI to accelerate and assure the safety of deployments; and Oxa Hub, a set of cloud-based offerings for autonomous fleet management. Our technology is being deployed across the UK and the U.S, and we’re partnering with a fast-growing ecosystem of operators, vehicle OEMs and equipment makers serving autonomous transportation globally as it advances.

Based in Oxford, and with offices in Canada and the U.S, Oxa was founded in 2014 and is growing rapidly (350+ ‘Oxbots’ to date). Our purpose is to change the way the Earth moves, through an uncompromising focus on safety, efficiency and explainability of our AI approaches. The company has attracted $225 million from leading investors so far, with $140 million raised in the last Series C funding round in January 2023.

Your Team

You will join a growing team of computer science and robotics experts leveraging machine learning, data and cloud infrastructure to build and deploy powerful on-vehicle reasoning capabilities. Your work will enable Oxa Driver™ to plan and execute sophisticated driving behaviours scalably across all of our customer domains using data-driven approaches.

Your Role

As our Senior Data Engineer (Reasoning ML), you will be responsible for creating and curating the datasets for training and evaluating our ML planner components. You will build effective data analysis tools and work across ML model development and evaluation to achieve desired AV driving behaviours. You will also actively participate in operational support for your team, ensuring the root causes of operational issues are identified and resolved, and drive improvements to product quality, customer experience, and maintainability.

You will:

Take a leading role within your team to develop and deploy state of the art data pipelines for our machine learning models.
Design and implement metrics for model validation and continuous monitoring in production.
Leverage the Oxa Metadriver™ platform to generate synthetic data, and train effective and robust driving policies,
Build cloud tooling and infrastructure in support of experimentation, evaluation and deployment workflows.
Engage with team members and colleagues throughout the business to create an environment that supports collaboration and mutual understanding.
Contribute to hiring and onboarding new team members, including mentoring and developing junior engineers.

Requirements

What you need to succeed:

Degree in Computer Science, Mathematics or a related field.
3+ years of professional experience developing behavioural machine learning technologies for autonomous vehicles or robotics.
Experience with production ML pipelines: data creation and curation, training frameworks, evaluation pipelines.
Fluency in Python and experience with data analysis libraries and packages.
Proven record of leading and delivering projects as part of a team.
Effective technical communication and leadership skills.
An appreciation for the role of safety, security and ethics in AI.

Extra kudos:

PhD or MSc in Computer Science, Mathematics, or related field.
Relevant publications or talks at industry conferences or in journals.
Familiarity with open benchmark datasets for autonomous vehicles (e.g., Waymo, nuScenes/nuPlan, Argoverse, Level 5, etc.)
Experience developing and fielding autonomous systems.
Familiarity with Google Cloud Platform.

The Candidate Journey: Multi-Step and Two-Way

No-one wants to feel like a square peg in a round hole, so this process is designed to give you every chance to get the measure of us, and us of you. The various stages give you every opportunity to show your unique strengths and qualities, and enables each of us to establish if we’re a good fit for the other. If the fit is good and you’re selected, you’re then in a position to do great work and thrive, which is what everyone wants.

Benefits

We provide:

Competitive salary, benchmarked against the market and reviewed annually
Company share programme
Hybrid and/or flexible work arrangements
An outstanding £3,000 flexible benefits including private medical insurance, critical illness coverage, life assurance, EAP, group income protection
Funded relocation support
Fully funded Visa sponsorship if required
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 promote an open and inclusive culture that empowers our Oxbots to bring their whole, authentic selves to work every day. Oxa is proud to be an inclusive organisation and, as such, we require all team members within our recruitment process to understand and deploy best practices focused on de-biasing the whole recruitment cycle. We also apply a neuro inclusive lens to our recruitment process and want each potential Oxbot to enjoy the best experience possible for them. Please share with us any individual needs or reasonable adjustments we may need to make in advance of commencing the interview process with us.

Learn more about our culture here

Why become an Oxbot?

Our team of engineers, mathematicians and experts in AI, machine learning and much else is truly world-class. They are solving the most exciting and important technological challenges of our times.

But as well as smarts, Oxbots have heart. 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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Senior Data Engineer (Reasoning ML)