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Machine Learning Data Scientist

4 months ago

Oxford, United Kingdom Oxa Full time

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

The Data Capture team aims to collect and curate the datasets which contain the variation and volume needed to robustly train and certify Oxa’s autonomous vehicle technology.  We aim to help define the problem of autonomous driving in data to enable easier adaptation of Oxa’s technology to new areas. 

Data Capture sits within the MetaDriver product group which 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. Data as with all AI and machine learning forms a crucial foundation for this as well as for all of Oxa’s technology.

Modern AI/ML relies on data. To solve a problem and more importantly prove that you have solved it you must define that problem in data In order to achieve Oxa's aim of Universal Autonomy, we must collect quality, varied data in volume. This is key not only to train the best autonomous vehicle systems but enables robust certification of their safety. 

Your Role

Our Data Scientists role is to optimise the deployment of a suite of data collection vehicles, developing novel ways to collect the most varied datasets, such as using automated route planning. You will be at the forefront of automating data curation pipelines using the latest machine learning techniques and optimising the use of manual labelling. Continually researching state-of-the-art data representations with self-supervised learning to explore and understand large datasets at scale and building certifiable dataset benchmarks which robustly prove different components of the autonomous technology stack.

Your Responsibilities

  • Vehicle Data Collection Improvements: Investigate ways of improving data capture within the vehicle. e.g. collecting voice recordings from the driver, collecting additional metadata and onboard processing of data to provide automated instructions to the driver.
  • Vehicle Logistics: Ensure that there is a clear plan for where and when the vehicles should drive and  collect data. Organisation of drivers, GCA copying etc. Ensure adherence to regulations etc.
  • Automated Data Labelling: Building automated data labelling pipelines to provide richest possible data labels which are ready for training.
  • Data Representation Learning: Researching the best representations of data to enable search, cleaning benchmark creation and data gap analysis.
  • Data Cleaning: Automatically clean data of any unwanted anomalies, understanding the cause of these anomalies and correcting the data collection process if needed.
  • Data Search: Enable searching of data to allow teams to easily find the data they need to solve a task. Hard example mining.
  • Data Gap Analysis: Automate the discovery of features and events that we have limited or no examples of. Develop methods for discovering the most efficient options for collecting new data to fill the identified gaps.
  • Data Benchmark Creation: Create robust benchmarks that test the capability of various algorithms. Different benchmarks will be needed to test different techniques and scenarios.
  • Offline Assurance and Benchmark Evaluation Tools: Develop software that enables standardisation of how we report performance of techniques on the various benchmarks. 
  • Contributing to high-quality, written, technical reports and visual media which represent progress and accomplishments in the company data agenda

Requirements

What you need to succeed

  • Software development skills in Python
  • A deep understanding of state-of-the-art Deep Learning theory and techniques
  • A deep understanding of datasets and what makes good and bad data benchmarks for machine learning.
  • Machine Learning skills for experimentation, model development, dataset exploration & cleaning
  • An ability to understand both technical and commercial requirements.
  • An appetite to get practical, you can only collect good data if you understand the full process, so expect to get stuck into the actual data collection, e.g. fixing issues on vehicles, working closely with drivers and perhaps doing some driving yourself.

Extra Kudos if you have

  • Familiarity with cloud platforms, preferably Google Cloud Platform (GCP)
  • Exposure to Machine Learning Ops (MLOps)
  • Development of self-supervised foundation models
  • Experience developing automated or efficient manual labelling pipelines
  • Experience working with lidar and multi-camera data
  • Hands on experience in data collection efforts in other companies 
  • Experience with certification of machine learning algorithms
  • Programming skills in C++
  • An understanding of the what data is needed across the company and for our partners
  • Practical experience with robotics

Benefits

We provide:

  • Competitive salary, benchmarked against the market and reviewed annually
  • 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
  • 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 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.

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, they 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.