Overview

Senior Machine Learning Engineer role at Lyst. This is a hybrid role combining deep data science expertise with production‑grade ML engineering, focused on unlocking smarter, more scalable advertising through automation and optimisation.

We’re looking for a commercially minded and technically strong ML Engineer to join our Product Listings team, responsible for designing experiments, building predictive models, and deploying them at scale to optimise product bidding and maximise profit across platforms like Google Shopping.

Role

This role involves the full ML lifecycle—from exploring large, messy datasets and engineering features, to evaluating models offline and running experiments to validate impact. You will build, deploy and monitor models in production with retraining workflows, pipeline orchestration, and performance alerts, supported by your tech lead and the wider Data Science chapter at Lyst.

We primarily use Python with standard ML toolkits (e.g., scikit‑learn, TensorFlow, PyTorch) and run ML code in AWS/SageMaker where possible. We value clean, documented, well‑tested, and reviewed code and have tooling to support this.

Responsibilities

• Productionise Machine Learning models into robust, maintainable systems—including retraining pipelines, monitoring, and performance alerting
• Build and evaluate ML models that support smarter paid marketing—e.g. product‑level ROAS prediction, lifecycle‑aware bidding, and grouping optimisation
• Explore large‑scale product and performance datasets to uncover insights, test hypotheses, and identify features that drive business value
• Work on all parts of the data science workflow: from data cleaning and exploratory analysis to offline model benchmarking and validation
• Collaborate with marketers to reduce manual overhead in campaign management while improving ad efficiency and profitability
• Improve our ad feed infrastructure to ensure product attributes, pricing and availability are optimised for campaign performance
• Contribute as needed to product data initiatives (e.g. classification, deduplication), especially where they impact ad quality or model input

Requirements

• 3+ years of experience building and deploying ML models in production
• Strong Python and SQL skills, with a solid understanding of data wrangling, feature engineering and model evaluation
• Deep understanding of the data science process—comfortable with exploratory analysis, statistical testing, and model comparison techniques
• Experience with structured prediction problems (e.g. regression, classification, ranking) using real‑world, often messy data
• Familiarity with advertising systems (Google Shopping, PMAX, etc.) and marketing metrics like ROAS, profit, and conversion is a strong advantage
• Experience productionising ML models—setting up training pipelines, versioning, monitoring and retraining

Benefits

• Our Ways of Working: We all come into the office on Tuesdays and Thursdays, with the option to work remotely or come into the office on the other days. We value in‑person collaboration and community spirit.
• Time Off: 29 holidays per year in addition to 8 statutory bank holidays; holiday year runs 1 April to 31 March
• Competitive Family Leave Package: Enhanced Family Leave, paid time off for dependents, and support for fertility treatment and loss
• Clothing Benefit: Annual clothing allowance starting at £250 and increasing with length of service
• Private Healthcare: Vitality comprehensive healthcare from day one
• Training Allowance: £1,000 annual training allowance for conferences, courses and resources
• Pension Scheme: The People’s Pension with at least 5% employee and 3% employer contributions
• Eye Tests and Vouchers: Free annual eye test and discount on glasses
• Cycle‑to‑Work Scheme: Bicycle purchase with voucher to collect
• Transport Season Ticket Loan: Interest‑free loan for travel
• Social Events: Frequent company‑wide and team social events and interest groups

Diversity and Inclusion

We want to build a world where fashion works for everyone and are committed to diversity and inclusion. We encourage applicants from all backgrounds to apply. We are happy to discuss flexible working arrangements.

Don’t meet every single requirement? We welcome you to apply anyway; you may be just the right candidate for this or other roles.