Software Engineer (Machine Learning - MLOps)

Tesco Poland; Kraków; On-site; PLN 180,000 - 260,000; Full time

Benefits offered by this job

Flexible working hours

Learning budget

Career progression

Job summary

Tesco Poland is seeking a Machine Learning Engineer to join our Data Science Engineering team. You will collaborate with engineers, data scientists, product managers, and operations teams to deliver scalable ML solutions that impact customers and run our business processes.

You will work across edge, cloud and big-data environments, contributing to toolchain development, deployment, and production-grade code. Strong Python, MLOps and cloud experience are preferred.

Qualifications

• Bachelor's degree in engineering, computer science, maths or science.
• Customer focus balancing outcome delivery and technical excellence.
• Experience building MLOps systems to market standards.
• Commercial experience in high-impact Data Science projects.
• Awareness of emerging MLOps practices and tooling.
• Analytical mindset to tackle business problems.
• Experience with multiple programming languages; fluent in Python.
• Version control using Git and SDLC tooling.
• Experience with monitoring/logging/alerting tools (e.g., Splunk, Grafana).
• Knowledge of data structures/algorithms.
• Experience with open-source Data-Science environments.
• Knowledge of open-source big-data technologies such as Apache Spark.
• Experience building cloud solutions, ideally Azure.
• Experience with Scrum & Kanban.
• Retail/logistics/ecommerce background advantageous.

Responsibilities

• Participating in group discussions on system design and architecture
• Translating needs into technical requirements with product teams
• Collaborating with Data Scientists, Software Engineers and Product teams across the lifecycle
• Delivering high-quality code and production-ready solutions
• Performing code reviews to optimize performance of data science solutions
• Supporting production systems, resolving incidents, and performing root cause analysis
• Evolving technology, processes and practices
• Sharing knowledge within the engineering team
• Collaborating on complex initiatives via working groups
• Improve and build solutions using GenAI
• Applying SDLC practices to create and release robust software

Skills

MLOps

Python

Git

Apache Spark

Azure

Scrum & Kanban

Open Source Tools

Monitoring tools

Data Science

Cloud computing

Education

Bachelor's or higher in CS/Engineering/Math/Science

Job description

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.

• Participating in group discussions on system design and architecture
• Working with product teams to communicate and translate needs into technical requirements
• Working alongside our Data Scientists, Software Engineers and Product teams across the software lifecycle
• Delivering high quality code and solutions, bringing solutions into production
• Performing code reviews to optimize technical performance of data science solutions.
• Supporting production systems, resolving incidents, and performing root cause analysis
• Look for how we can evolve and improve our technology, processes and practices
• Sharing knowledge with the immediate engineering team
• Collaborate with other teams on more complex initiatives via working groups
• Improve and build solutions using GenAI
• Applying SDLC practices to create and release robust software

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.
• Demonstratable 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.
• 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.

Our colleagues work with one goal in mind, helping to make every day a little better for our customers, colleagues and communities all over the world. No two customers are the same, neither are our colleagues.

At Tesco, we champion a balance that lets you thrive both in and out of work. Spend 60% of your week collaborating with colleagues at our office locations or local sites and the rest remotely. Whether you're just kicking off your career, juggling passions, or navigating big life events, we're here to support you.

Tesco is committed to celebrating diversity and everyone is welcome at Tesco. As a Disability Confident Employer, we’re committed to providing a fully inclusive and accessible recruitment process, allowing candidates the opportunity to thrive and inform us of any reasonable adjustments they may require.

Want to get to know us better? Watch our team talk about our culture – YouTube

What our colleagues like the most at Tesco:

• We develop our own products
• We make an impact; large scale of operation
• Accountability and respect are given to us
• We cooperate and support each other
• There are great colleagues who are divided into small teams here
• We can develop and learn new things

Discover how our colleagues shape Tesco’s tomorrow.