Your Role

Researching and developing state of the art pipelines for scenario synthesis, reinforcement learning, motion prediction, representation learning Contributing to tooling and processes for benchmarking, filtering, visualisation and comparison of synthetically generated driving scenarios Developing state of the art techniques and processes for assuring data coverage Keeping up with the latest advances in Machine Learning research, and applying relevant techniques to Oxa MetaDriver Contributing to the development tools and process to support the scenario synthesis, acquisition of data, software-in-loop simulation and ML frameworks Developing model optimisation techniques Developing data visualisation tools 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 drive for efficiency around use of data in the company Contributing to the effort in making sure the right data is available at the right time across our technology platform, for our development processes, and 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.

Requirements

What you need to succeed:

A deep understanding of Reinforcement Learning Experience with one or more of: Imitation Learning, Representation Learning, Unsupervised Learning Experience with Machine Learning in a research environment Demonstrate proficiency in Python software development skills Machine Learning skills for data amplification and synthesis Solid software engineering design principles and up-to-date knowledge of Python best practices An ability to understand both technical and commercial requirements.

Extra kudos will be awarded for:

Experience with efficiently benchmarking and validating synthetic data Familiarity with cloud platforms, preferably Google Cloud Platform (GCP) Experience with MLOps Experience working with driving simulators, autonomous driving software, or traffic modelling Familiarity with C or C++

Benefits

We provide:

Competitive salary, benchmarked against the market and reviewed annually Company share programme Hybrid and/or flexible work 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 flexible £2,000 (pro-rata) benefits fund to spend on additional benefits of your choice, including tech scheme and cycle to work benefits 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