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 alertingBuild and evaluate ML models that support smarter paid marketing—e.g. product-level ROAS prediction, lifecycle-aware bidding, and grouping optimisationExplore large-scale product and performance datasets to uncover insights, test hypotheses, and identify features that drive business valueWork on all parts of the data science workflow: from data cleaning and exploratory analysis to offline model benchmarking and validationCollaborate with marketers to reduce manual overhead in campaign management while improving ad efficiency and profitabilityImprove our ad feed infrastructure to ensure product attributes, pricing and availability are optimised for campaign performanceContribute as needed to product data initiatives (e.g. classification, deduplication), especially where they impact ad quality or model inputRequirements

3+ years of experience building and deploying ML models in productionStrong Python and SQL skills, with a solid understanding of data wrangling, feature engineering and model evaluationDeep understanding of the data science process—comfortable with exploratory analysis, statistical testing, and model comparison techniquesExperience with structured prediction problems (e.g. regression, classification, ranking) using real-world, often messy dataFamiliarity with advertising systems (Google Shopping, PMAX, etc.) and marketing metrics like ROAS, profit, and conversion is a strong advantageExperience productionising ML models—setting up training pipelines, versioning, monitoring and retrainingBenefits

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 MarchCompetitive Family Leave Package:

Enhanced Family Leave, paid time off for dependents, and support for fertility treatment and lossClothing Benefit:

Annual clothing allowance starting at £250 and increasing with length of servicePrivate Healthcare:

Vitality comprehensive healthcare from day oneTraining Allowance:

£1,000 annual training allowance for conferences, courses and resourcesPension Scheme:

The People’s Pension with at least 5% employee and 3% employer contributionsEye Tests and Vouchers:

Free annual eye test and discount on glassesCycle-to-Work Scheme:

Bicycle purchase with voucher to collectTransport Season Ticket Loan:

Interest-free loan for travelSocial Events:

Frequent company-wide and team social events and interest groupsDiversity 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.

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