Senior Machine Learning Engineer, Cleo AI

• 4+ years of experience in data science, machine learning engineering, or related roles
• Excellent knowledge of both Data Science (Python, SQL) and production tools
• A deep understanding of probability and statistics fundamentals
• Big picture thinking to correctly diagnose problems and find a path to getting measurable impact out of machine learning
• Top tier communication skills, to be able to partner with Product and Commercial Leaders and communicate findings to non-technical stakeholders
• Proficiency in cutting edge natural language processing techniques, such as fine-tuned transformer models, text classification, semantic search, and LLM integrations
• Experience deploying machine learning models into production and monitoring their performance

Desirable

• Machine Learning Engineers at Cleo work on building novel solutions to real-world problems. This really does vary but could be: creating chatbots to coach our users around their financial health, creating classifiers to better understand transaction data or even optimising transactions within our payments platform
• Ultimately, we’re looking for a brilliant Machine Learning Engineer to join us on our mission to fight for the world's financial health. You’ll be leading technical work within a team of adaptable, creative and product-focused engineers, who train & integrate cutting edge machine learning across a variety of products and deploy them into production for millions of users. We understand our customers, we understand their pain, and we are passionate about helping them
• Here are some examples, big and small, of the kinds of product feature work our ML Engineers have taken part in over the last year:
• Designed and implemented AI agents to analyse and extract insights from users’ transactional data
• Developed models to interpret transactional data, enhancing the understanding of users’ finances. Think about your bank statement—how often do you not recognise a transaction on first review?
• Engineered long-term memory for the chatbot, using LLM summarization, text classification, and a vector database
• Implemented contextual bandit systems that test new chat content and drive engagement by personalising Cleo’s messages
• Built models to evaluate risk based on bank transaction features and user activities
• Developed optimisation models to improve payment success rates for customers while minimising business costs, tackling this as a two-sided optimisation challenge
• Whatever problem you tackle, and whichever team you join, your work will directly impact those most in need, helping to improve their financial health