Senior Machine Learning Engineer

We work together. Your team and the people you will work with…

We work in small, fully autonomous teams that have real ownership of their products. We use the best tool for the job and constantly look for better.

We are seeking a production-focused Machine Learning Engineer to bridge the gap between data science research and scalable, reliable software.

In this role, you will partner with Data Scientists to re-architect experimental models (POCs)—such as Next Best Action and Churn Propensity—for production. You will own "Day 2" operations including deployment, latency optimization, and monitoring, while also building the infrastructure for GenAI and RAG applications powering our tools.

We Deliver Progress.. What you'll do and how you'll make an impact..

As a Machine Learning Engineer at UW, your responsibilities will include:

• Predictive Modelling: Design and deploy robust ML models to solve business challenges, specifically Churn Propensity and Next Best Action (NBA) engines.
• Customer Analytics: Develop advanced Customer Segmentation using clustering techniques to tailor services and communications.
• Commercial Valuation: Own xLTV and ROI logic, modeling long-term customer value to optimize acquisition and retention spend.
• Deployment & Ops: Collaborate with Data Engineers to productionise scalable models, ensuring continuous monitoring for drift and performance.
• Experimentation: Design and analyse A/B tests to validate model effectiveness and measure commercial uplift.
• Stakeholder Partnership: Translate complex statistical outputs into actionable insights for Marketing, Product, Commercial and Ops stakeholders.