Senior Machine Learning Engineer (AI)

TL;DR

Senior Machine Learning Engineer (Python/MLOps): Productionizing experimental ML models for churn propensity and next best action engines with an accent on scalability, reliability, and deployment. Focus on bridging the gap between data science research and production software and building infrastructure for GenAI and RAG applications.

Location: London, United Kingdom. No visa sponsorship available.

Company

hirify.global (UW) is a utilities aggregator providing energy, broadband, mobile, and insurance in one place to help customers save time and money.

What you will do

• Design and deploy robust ML models to solve business challenges, specifically Churn Propensity and Next Best Action (NBA) engines.
• Develop advanced customer segmentation using clustering techniques to tailor services and communications.
• Own xLTV and ROI logic, modeling long-term customer value to optimize acquisition and retention spend.
• Collaborate with Data Engineers to productionize scalable models and implement continuous monitoring for drift and performance.
• Design and analyze A/B tests to validate model effectiveness and measure commercial uplift.
• Translate complex statistical outputs into actionable insights for Marketing, Product, and Commercial stakeholders.

Requirements

• Proven experience deploying Machine Learning models into high-traffic production environments.
• Strong proficiency in Python and software engineering best practices (unit testing, modular code, Git).
• Essential experience with containerization using Docker and Kubernetes.
• Experience with MLOps tooling such as model registries and monitoring tools (e.g., MLflow, Grafana).
• Must have the right to work in the UK; visa sponsorship is not provided.

Nice to have

• Experience with Feature Stores (e.g., Feast, Tecton).
• Knowledge of streaming data technologies like Kafka and PySpark.
• Hands-on experience building or deploying LLM-based applications with RAG architectures and vector databases.

Culture & Benefits

• Optional four-day working week (90% pay for 90% impact).
• Annual discretionary performance bonus ranging from 15-40%.
• Flexible working arrangements and the ability to work abroad for up to three weeks, twice a year.
• Dedicated learning and development budget with bi-annual promotion cycles.
• Eight-week paid sabbatical after four years of service.
• Comprehensive benefits including private health, dental insurance, or gym membership allowance.