Software Engineer (Machine Learning - MLOps)
About the role
We are looking for a Machine Learning Engineer, to join our growing Data Science Engineering team. 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.
This role would suit someone with previous experience working as a ML Engineer / Data Science Engineer.
About the Team
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, develop data products at scale and maintain existing applications.
Our Data Science team are involved in a broad range of projects, spanning across supply chain, logistics, store and online. These include projects in the areas of Operations Optimizations, Commercial Decision Support (e.g. Forecasting, Range Optimization, Supply Chain support), 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 optimization through to deployment of solutions on the edge, cloud and big-data environments.
What is in it for you
- Permanent contract from the go – as a sign of our trust in your abilities
- MacBook as your tool for work
- Learning opportunities - certified technical training and learning platforms like Udemy
- Referral Bonus
- Sports activities with a personal trainer in the office
- Additional 4 days of paid leave to support your well-being and family life
- Up to 20% yearly salary bonus – based on both individual and business performance
- Private healthcare (LuxMed)
- Cafeteria & Multisport
- Supporting those, who are not yet eligible for full holiday entitlement, by expanding their pool from 20 to 25 days
- IP Tax Deductible Costs
If that sounds exciting, then we'd love to hear from you!
You 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.
- Demonstrable experience of building MLOps systems according to the best market standards.
- 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.
- knowledge of ML workflow/orchestration platform like Airflow
- 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.
- A background or strong understanding of the retail sector, logistics and/or ecommerce would be advantageous but is not required.
Unsure if you fit all the criteria? Apply and give us the chance to evaluate your potential – you could be the perfect fit!