Data Scientist; Operational Domain Intelligence

Oxais 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 Meta Driver, 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

Oxa Foundry is a suite of tools that combines generative AI, digital twins and simulation to accelerate machine learning and testing of self-driving technology before and during real-world use. Tools within Oxa Foundry are also unlocking new opportunities to launch innovative solutions for industries such as commercial fleet insurance and risk management. Leveraging Oxa's experience of deploying AVs and establishing capabilities to safely scale (by identifying, quantifying and managing route risk with limited or no pre-existing data), we are helping organisations in those markets augment and generate new data to develop transformative fleet risk management solutions for their own customers.

Your team will ensure the company has enough data of the right kind and the right time from the right sources to sustain rapid improvement across all its tools. It will ensure suitable data ownership across our own fleet and via our customers and partners using data synthesis and expansion, simulation, automatic annotation and logging where appropriate.

Your Role

• Researching and developing state of the art pipelines for: analysing deployment domains, route feasibility checks, domain clustering and classification, representation learning and data coverage analysis.
• Research and development with foundational models for data generation and understanding.
• Responsible for data interpretation, data governance, communicating findings from the validation, and creating dashboards for metrics management.
• Contributing to the creation of appropriate data tools that support, amplify, and accelerate our scaling of our system for development, testing, and commercial requirements.
• Contributing to the effort in making sure the right data is available at the right time across our technology platform, for our deployments while in use with customers and partners.
• Working with other teams and leads in facilitating the creation of specialist tooling and process supporting the company wide data-agenda in both the data team and in specialist teams.
• Keeping up with the latest advances in computer vision and tracking research and applying relevant techniques to Oxa Meta Driver.
• Contributing to the backlog items that the team manages.
• Contributing to regular stand ups, team meetings, and 1-2-1's as part of your role.

Requirements

What you need to succeed:

• Experience with Machine Learning in a research environment.
• Demonstrate proficiency in Python software development skills.
• Experience working with LLMs, VLM and other large scale models.
• Solid software engineering design principles and up-to-date knowledge of Python best practices.
• An ability to understand both technical and commercial requirements.
• Statistical analysis, introspection and validation on large datasets.

Extra Kudos if you have:

• Experience with efficiently benchmarking and validating synthetic data.
• Machine Learning skills for data amplification and synthesis.
• Familiarity with cloud platforms, preferably Google Cloud Platform (GCP).
• Experience with computer…