Senior Machine Learning Engineer – Welwyn Garden City, United Kingdom of Great Britain and Northern Ireland

Overview

You will drive the delivery of scalable ML-enabled products within Tesco’s strategic data and analytics technology area. You’ll collaborate with engineers, data scientists, product managers, and analytics professionals to turn needs into production-ready solutions. You’ll contribute across the software lifecycle, shaping architecture and improving production systems. This is a chance to impact customer experiences and operations at scale through data-driven innovations.

Pay / Benefits

• Annual bonus up to 20%
• Holiday 25 days + personal day + bank holidays
• Private medical insurance
• Maternity/Adoption leave 26 weeks + 13 weeks statutory
• Paternity leave 6 weeks
• 24/7 virtual GP and EAP

Responsibilities

• Participate in system design and architecture discussions
• Translate product needs into technical requirements with cross-functional teams
• Collaborate across software lifecycle with data scientists, engineers and product teams
• Deliver high-quality code and production-ready solutions
• Perform code reviews to optimise data science performance
• Support production systems, resolve incidents and perform root cause analysis
• Continuously evolve technology, processes and practices
• Share knowledge with the wider engineering community
• Apply SDLC to release robust software

Key requirements

• Higher degree in engineering, computer science, maths or science
• Customer-focused with balance between outcomes and technical excellence
• Ability to apply technical skills to real-world problems
• Experience building scalable and resilient software systems
• Experience leading a small engineering team
• Commercial experience on high-impact data science projects in complex organisations
• Experience in MLOps; feature stores and model lifecycle management advantageous
• Proficiency in at least one programming language (preferably Python)
• Understanding of data structures and algorithms
• Experience with version control (Git) and lifecycle tooling
• Experience with monitoring/logging/alerting tools (e.g., Splunk, New Relic, Grafana)
• Experience with Spark, Databricks, Snowflake, or BigQuery for big-data transformations
• Cloud-based solutions, ideally Azure
• Experience with Scrum & Kanban software methodologies

• Customer focus
• Cross-functional collaboration
• Knowledge sharing
• Python (preferred)
• MLOps tooling and practices
• Data structures & algorithms

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