Within Tesco Data & Analytics, 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 teams are 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). Our Machine Learning Engineers 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 a 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.
Responsibilities
- Participating in 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 looking for how we can evolve and improve our technology, processes and practices.
- Sharing knowledge with the wider engineering community.
- Applying SDLC practices to create and release robust software.
You'll come from either an Engineering or Data Science background, with a good understanding of the Data Science Toolkit (Programming, Machine Learning, MLOps etc) and bringing data science solutions into production. You therefore tick the majority of the following points:
Key Requirements
- A higher degree in engineering, computer science, maths or science.
- 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. The ideal candidate is fluent in 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.
Working patterns
We’re a big business and we can offer a range of diverse full‑time & part‑time working patterns across our many business areas, which means that we can find something that works for you. We work in a more blended pattern – combining office and remote working. Our offices will continue to be where we connect, collaborate and innovate. If you are applying internally, please speak to the Hiring Manager about how this can work for you – Everyone is welcome at Tesco.
#J-18808-Ljbffr”, “datePosted”: “2026-05-16”, “hiringOrganization”: { “@type”: “Organization”, “name”: “WeAreTechWomen”, “sameAs”: “https://uk.whatjobs.com/pub_api__cpl__433586687__4861?utm_campaign=publisher&utm_medium=api&utm_source=4861&geoID=199” }, “jobLocation”: { “@type”: “Place”, “address”: { “@type”: “PostalAddress”, “addressLocality”: “Welwyn Garden City” } } }Within Tesco Data & Analytics, 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 teams are 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). Our Machine Learning Engineers 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 a 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.
Responsibilities
- Participating in 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 looking for how we can evolve and improve our technology, processes and practices.
- Sharing knowledge with the wider engineering community.
- Applying SDLC practices to create and release robust software.
You’ll come from either an Engineering or Data Science background, with a good understanding of the Data Science Toolkit (Programming, Machine Learning, MLOps etc) and bringing data science solutions into production. You therefore tick the majority of the following points:
Key Requirements
- A higher degree in engineering, computer science, maths or science.
- 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. The ideal candidate is fluent in 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.
Working patterns
We’re a big business and we can offer a range of diverse full‑time & part‑time working patterns across our many business areas, which means that we can find something that works for you. We work in a more blended pattern – combining office and remote working. Our offices will continue to be where we connect, collaborate and innovate. If you are applying internally, please speak to the Hiring Manager about how this can work for you – Everyone is welcome at Tesco.
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