Senior Machine Learning Engineer

About the JobSet the modelling and experimentation direction across the Central Product and Platforms funnel and personally lead the highest-stakes problemsArchitect systems that hold up at the scale of millions of bookings and a global user base, owning the hard trade-offsMake the call on contentious short-term technical questions, from metric definitions to model architecture, across the domainResolve the measurement and modelling problems that block whole teams, and define the patterns they then reuseInfluence Central Product and Platforms product and business strategy with a data-science perspective leaders trustFind where existing models, pipelines, or metrics quietly cost the business at scale, and drive the fixMentor senior scientists and raise the technical bar across the domain through review and exampleJob RequirementsYou have at least 10 years of relevant experience.You have the deepest technical command of Python and the ML/stats stack (scikit-learn, LightGBM, XGBoost, deep learning and optimisation where relevant)You write advanced SQL and architect the large-scale data and feature systems whole teams rely onYou take the most ambiguous, domain-spanning problems and turn them into the bets the funnel is organised aroundYou have authoritative command of search, recommendation, ranking, and pricing systems at marketplace scaleYou understand Central Product and Platforms economics deeply and anticipate the second- and third-order effects of a model changeYou design and adjudicate sophisticated experimentation and own the measurement standard others defer toYou set technical direction across teams through influence, judgment, and decision authority on the issues in your remitYou hold a degree in a quantitative field (Master’s or higher preferred) or equivalent, and influence senior cross-functional leadersYou work confidently with cloud (GCP preferred) and production ML, and set the bar for AI-assisted ways of workingYou have a track record of models that delivered large, attributable business impact at marketplace scaleYou have designed an internal ML platform, feature store, or experimentation framework that changed how teams buildYou have worked on marketing or commercial measurement (MMM, MTA, propensity, CLV) that informed real spend or pricing decisions