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Cleo
Principal Machine Learning Engineer - Chat
£111k
- £145k
London
Hybrid
Description
Hybrid requirements: This role has flexible working patterns.
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 Principal 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.
What you’ll be doing
Training and fine-tuning models to solve customer problems across our chatbot and the bank transaction data behind it.
Deploying these models into our production environments using our in-house ML platform, which you can read about on our blog: Let’s have an Espresso: MLOps at Cleo. Or integrate with LLMs hosted by OpenAI, Anthropic, GCP, AWS and others.
Working cross-functionally with backend engineers, data analysts, UX writers, product managers, annotation teams, and others to ship features that improve our users’ financial health.
Taking the initiative to propose & lead technical work towards problems that were previously unknown or poorly understood. Driving change at the pillar and chapter level that affects multiple squads.
Keeping Cleo at the forefront of NLP by driving the adoption of appropriate state-of-the-art techniques and communicating the team’s successes and learnings at the company level & beyond.
Mentoring & advising colleagues on their choices of models, architecture, and evaluation, promoting best practices for how we use LLMs.
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:
Building AI Agents to explore and derive insights from users transactional data
Developed deeper understanding of users finances through models extracting meaning from transactional data. Think about your bank statement, how often do you not know what a transaction is?
Developed contextual intent classifiers to understand what conversations users are having with Cleo, enabling control of how Cleo should respond
Building ML models to understand the actions that users have available to them in Cleo and provide those contextually in conversations
Built ML models to understand the risk of customers using bank transaction features and user activity
Built models to optimise the payment success for our customers and optimising the costs for the business. Think of this as a two-sided optimisation problem.
Whatever problem you tackle, and whichever team you join, your work will directly impact those most in need, helping to improve their financial health.
What you’ll need
Experience in industry machine learning roles as a technical leader or principal/staff engineer
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 productionising research
Top tier communication skills, to be able to partner with Product and Commercial Leaders
Industry-leading contributions to your field, communicated through conferences, blogs, talks, or open-source projects
Nice to have
Advanced Degree in a quantitative discipline
Strong experience with additional programming languages, such as Java, Scala, C++
Broader contributions to your field through: conferences, blogs, talks, or open-source projects.
Role tech stack
Cleo
Principal Machine Learning Engineer - Chat
£111k - £145k
London
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