Our teams are putting the world’s retailers online using the cloud, robotics, AI, and IoT. We provide services to partner clients globally via our innovative advanced robotics technology, known as the Ocado Smart Platform (OSP), this drives our highly automated, multi-million pound Customer Fulfilment Centres (CFCs). In our CFCs together with the proprietary software applications - we operate a world-class online grocery business that automates the single pick of products, ready for your online delivery.
About the role:
As a Machine Learning Engineer you will work closely with the team lead, management, data scientists and software engineering teams to identify, scope, plan and manage projects, and effectively communicate complex technical issues and findings to a range of technical and non-technical internal audiences. You will deal with a wide range of problems and have a real impact on the operational performance of the company and you will be given autonomy in how you approach these problems.
Data Science/Machine Learning Work
You will responsible for most areas touched by data science, including: experimentation with features and parameters; feature engineering; analysis; testing, data assertions and monitoring; and (simple) modelling.
You will also be responsible for the following engineering/DevOps areas: setting up data science projects with their necessary configuration, permissions, etc.; setting up data pipelines; integrating ML solutions; giving suggestions for best possible ways of development and deployment of ML models; solving performance and other issues related to the whole project; and helping with integration of ML solutions with other services.
In addition, you will be expected to promote good engineering practices, bug prevention strategies, testability, fixing security vulnerabilities where appropriate, and other advanced quality concepts.
Tech stack: Java, Python, AWS, Terraform, GitLab CI/CD;
Google Cloud Platform: BigQuery, BQML, Vertex AI, Dataflow (Apache Beam), Dataproc (Spark)
Communication is of utmost importance; you will be in contact with business stakeholders and will need to work with developers both within the team and in other technology teams to ensure that your solutions are properly productionised and can be supported easily by other members of the team.
You hold a degree in Computer Science, Mathematics, Statistics, or other quantitative sciences. You are experienced in building productionised machine learning models at scale with a preference for MVP and iteration. We expect you to be able to demonstrate computer-programming ability including fluency in two or more of Python, Java (or equivalent), and SQL. Additionally, a solid understanding of basic statistical and machine-learning concepts is also required.
It would be desirable if you met the following criteria:
Holding a portfolio of past work (applications, analysis, visualisations, blog posts, presentations etc.). It would be advantageous if you are experienced with Google Cloud Platform and knowledgable of common machine learning toolkits (e.g. scikit-learn). Besides, it is highly appreciated if you have experience conducting research and analysis on large data sets and providing interpretations of the results, plus the ability to model complex problems mathematically and/or computationally.
What do I get in return:
Flexible working hours with short Fridays
Reduced hours in August
Private Health Insurance
Flexible WFH policy
Gym membership discounts
Fresh fruit, snacks, tea and coffee
Monthly social events
Table football, board games and Nintendo Switch
Tech Talks and internal trainings
English, Spanish and Catalan language courses