Senior ML Engineer (Search & Recommendation)

We have an exciting opportunity for a Senior ML Engineer to join our growing Data Science Engineering team where you will work on our Online Search & Recommendations projects. As the technical expert on our Search & Recs programme you will work alongside our data scientists, helping with everything from development of tools and platforms, code optimisations through to deployment of solutions on the edge, cloud and big-data environments as well as helping to grow the Engineering team and supporting junior members of the team.

About the Team:

Within our Data Science & Analytics team, we help our customers and the communities where we operate get the most value from data. We build and run Tesco’s data platforms, we architect and engineer data onto these platforms, provide capabilities and tools to the analytics community across Tesco, and develop data products at scale. 

Our Data Science Engineering team is involved in a broad range of projects, spanning across supply chain, logistics, store and online.  These include projects in the areas of Operations Optimisations, Commercial Decision Support (e.g. Forecasting and Range Optimisation), Online (e.g. Search and Recommendation) and Intelligent Edge (e.g. Computer Vision). 

As a Senior Machine Learning Engineer, you’ll be a significant contributor to the delivery of products in one of Tesco’s most strategic technology areas. You’ll work with other engineers, data scientists, product managers, systems engineers, and analytics professionals to help deliver valuable and innovative outcomes for our customers. You’ll work within and across our Engineering and Data Science teams, delivering scalable products that improve how we serve our customers and run our operations. 

In this role, you will join our Search and Recommendation programme, with responsibilities including:

• Leading and supporting group discussions on system design and architecture.
• Working with product teams to communicate and translate needs into technical requirements.
• Working with Data Scientists, Engineers and Product teams across the software lifecycle.
• Delivering high quality code and solutions, bringing solutions into production.
• Performing code reviews to optimise technical performance of data science solutions.
• Supporting production systems, resolving incidents, and performing root cause analysis.
• Continually look for how we can evolve and improve our technology, processes and practices.
• Sharing knowledge with the wider engineering community.
• Mentoring and developing others around you, leading a team of engineers.
• Applying SDLC practices to create and release robust software

• A background or strong understanding of the retail sector, logistics and/or ecommerce.
• Practical experience with search technologies and recommender systems
• Experience leading technical conversations and mentoring and leading others
• Customer focus with the right balance between outcome delivery and technical excellence.
• The ability to apply technical skills and know-how to solving real world business problems.
• Demonstratable experience of building scalable and resilient systems.
• Commercial experience contributing to the success of high impact Data Science projects within complex organisations.
• Awareness of emerging MLOps practices and tooling would be an advantage e.g. feature stores and model lifecycle management.
• An analytical mind set and the ability to tackle specific business problems.
• Experience with different programming languages and a good grasp of at least one language, ideally Python.
• Use of version control (Git) and related software lifecycle tooling.
• Experience with tooling for monitoring, logging and alerting e.g. Splunk or Grafana.
• Understanding of common data structures and algorithms.
• Experience working with open-source Data-Science environments.
• Knowledge of open source big-data technologies such as Apache Spark.
• Experience building solutions that run in the cloud, ideally Azure.
• Experience with software development methodologies including Scrum & Kanban.
• A degree in engineering, computer science, maths or science

We offer excellent benefits that help make Tesco a great place to work!  These include but are not limited to:

• Annual bonus scheme
• Holiday starting at 25 days plus a personal day (and bank holidays)
• Great colleague discounts and deals, saving you money on everyday purchases, utility bills for the home and more
• Retirement savings plan – save between 4% and 7.5% and Tesco will match your contribution
• Buy as you earn and Save as you earn share schemes
• Opportunities to get on – take advantage of our ongoing learning opportunities and award-winning training to help you achieve the career you want

Our vision at Tesco is to become every customer’s favourite way to shop, whether they are at home or out on the move.  Our core purpose is “Serving our customers, communities and planet a little better every day”.  Serving means more than a transactional relationship with our customers.  It means acting as a responsible and sustainable business for all stakeholders, for the communities we are part of, and for the planet.

We are proud to have an inclusive culture at Tesco where everyone truly feels able to be themselves.  At Tesco, we not only celebrate diversity, but recognise the value and opportunity it brings.  We’re committed to creating a workplace where differences are valued, and make sure that all colleagues are given the same opportunities.  We’re a big business with diverse working patterns and many business areas which means that we can find something that works for you.  Everyone is welcome at Tesco.

We have recently announced that we are moving to a more blended working week – combining office and remote working.  Our offices continue to be where we connect, collaborate and innovate.  Talk to us about how this can work for you.

Note: Should you be successful in your application, your employment will be subject to and conditional upon you providing your bank account details on your agreed start date.