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Cleo

Cleo

www.meetcleo.com

3 Jobs

394 Employees

About the Company

Cleo. Where AI meets money.

Cleo launched in 2016 by people who have been burned by banks. Fed up with the broken system, we decided it was time to make a change.

Since then, the cost of living has skyrocketed, the rich have continued getting richer, and our vision has only become clearer.

Our mission? To change the world's relationship with money.

Cleo is a platform for the 99% – an AI assistant defining a new category, one that goes beyond saving and budgets to actually changing how we feel about our finances.

Using simplicity and humor, she’s helped millions of people improve their relationship with money, because we believe that everyone has the potential to achieve financial well-being in just one generation.

Through a personalized chat, she provides you with deep insight about your money and tailored financial tools that increase your ability to save, all while making you laugh.

We’re a product for the next generation. That means that we are committed to inclusive and unbiased financial growth for all. It also means dropping the BS.

In the past year or so we’ve grown the Cleo team from 100 to 250+, and closed a $80m Series C led by Sofina (that’s a $500M valuation).

Want to get involved?

You know that awful feeling when you wake up wondering if what you’re about to do for the next 8 hours actually matters? That doesn’t happen here much.

Everything we do is grounded in purpose. And because we’re all showing up for the same reason, collaboration comes easy.

We have a culture of stepping up. We want, and expect you to grow and develop. You’ll have our support in everything you do. But more importantly, you’ll have our trust.

We treat our people as humans first, employees second, which means giving everyone a voice. All perspectives are embraced here.

Listed Jobs

Company background Company brand
Company Name
Cleo
Job Title
Machine Learning Engineering Manager
Job Description
Job Title: Machine Learning Engineering Manager Role Summary: Lead and grow a high‑performance ML engineering squad that designs, builds, and deploys production‑grade models, with a focus on natural language processing and large language models for a conversational financial product. Expectations: • Deliver end‑to‑end ML solutions that scale to millions of users. • Own the ML roadmap, translating business objectives into technical initiatives. • Hire, coach, and retain top ML talent. • Keep abreast of cutting‑edge research and evaluate new technologies for product impact. Key Responsibilities: • Define and prioritize the ML roadmap for the chat feature and related product lines. • Design, prototype, and deploy robust, production‑ready ML models in Python. • Oversee model monitoring, performance tuning, and continual improvement based on customer behavior data. • Mentor and develop ML engineers, ensuring skill growth and alignment with team goals. • Manage recruiting, headcount planning, and resource allocation for the ML squad. • Communicate technical findings and strategy to non‑technical stakeholders in a clear and concise manner. • Coordinate cross‑functional collaboration between product, engineering, and data teams. Required Skills: • Proven experience building and deploying production ML models (Python, Docker, Kubernetes). • Experience leading and developing high‑performing data science/ML engineering teams. • Deep knowledge of NLP, LLM evaluation, fine‑tuning, and transformer architectures. • Familiarity with container orchestration (Kubernetes), containerization (Docker), and vector search systems (OpenSearch, etc.). • Strong software engineering fundamentals and ability to write clean, production‑ready code. • Excellent communication, stakeholder management, and coaching abilities. Required Education & Certifications: • Bachelor’s or Master’s degree in Computer Science, Engineering, Applied Mathematics, or a related quantitative field. • No specific certifications required, but industry‑relevant courses or certifications in ML/AI are advantageous.
United kingdom
Remote
10-11-2025
Company background Company brand
Company Name
Cleo
Job Title
Graduate Machine Learning Engineer
Job Description
**Job Title:** Graduate Machine Learning Engineer **Role Summary** Build and deploy machine‑learning models that enhance credit, payments, risk, and conversational AI across a fintech platform. Work with a cross‑functional squad to turn business problems into data‑driven solutions, integrate large‑language models, and maintain model performance in production. **Experiences & Expectations** - Recent graduate with a strong foundation in machine‑learning concepts and programming. - Proven ability to develop, evaluate, and iterate models in a fast‑moving product environment. - Eager to learn production‑grade MLOps, monitoring, and data‑driven experimentation. - Strong collaboration with backend, frontend, data‑analytics, and design teams. **Key Responsibilities** - Design, train, and evaluate ML models for risk scoring, payment optimization, intent classification, and contextual recommendation. - Integrate LLMs for conversational agents and intent understanding. - Deploy models into production using the company’s in‑house ML platform; containerize pipelines (Docker, Kubernetes). - Implement monitoring for feature drift, accuracy, and API performance; troubleshoot and iterate. - Emit structured data for every feature to enable end‑to‑end observability and product improvements. - Conduct A/B tests or controlled experiments to validate business impact. - Collaborate in sprint planning, code reviews, and continuous delivery cycles. **Required Skills** - Python programming; experience with scikit‑learn, PyTorch, or TensorFlow. - MLOps fundamentals: model packaging, CI/CD pipelines, containerization, orchestration. - Data engineering basics: SQL, data preprocessing, feature engineering. - Understanding of supervised/unsupervised learning, evaluation metrics, hyper‑parameter tuning. - Exposure to LLMs (e.g., OpenAI, HuggingFace) and fine‑tuning practices. - Strong analytical mindset; ability to translate business goals into algorithmic solutions. - Version control with Git; experience with cloud services (AWS, GCP, Azure) is a plus. **Required Education & Certifications** - Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field. - No mandatory certifications, but ML or data‑science certifications (AWS Certified Machine Learning, GCP Professional Data Engineer, etc.) are valued.
London, United kingdom
Hybrid
Junior
16-12-2025
Company background Company brand
Company Name
Cleo
Job Title
Product Analyst, Fraud
Job Description
Job Title: Product Analyst, Fraud Role Summary: Leverage data-driven insights to reduce fraud, safeguard revenue, and enhance user experience across a rapidly scaling fintech platform. Work cross‑functionally with fraud investigators, engineering, product, and data science teams to define, model, and monitor fraud metrics, optimize rules, pilot third‑party data sources, and run A/B tests for continuous improvement. Expectations: - Deliver actionable analytics that inform fraud strategy and support sustainable growth. - Develop and maintain dashboards, KPIs, and recurring reports that track fraud risk and effectiveness of controls. - Identify, model, and test fraud patterns, recommending rule changes and new detection mechanisms. - Collaborate with internal partners and external vendors to integrate risk data and enhance decision‑making. - Communicate findings and strategic recommendations to stakeholders across product and business units. Key Responsibilities: - Define fraud metrics, track KPIs, and assess risk impact on the company and users. - Analyze user behaviour and payment data to uncover indicators of fraud. - Work with fraud investigators to identify trends, optimize existing rules, and create new rules. - Partner with engineering, product, and data science teams to build and improve fraud prevention, detection, and response frameworks. - Evaluate third‑party partners for supplemental customer data and risk precision. - Design and run A/B experiments to refine fraud strategies and improve user experience. - Support strategic planning, roadmap development, and prioritization of fraud initiatives. Required Skills: - Quantitative analysis experience in a digital product environment. - Strong SQL expertise for extracting insights from complex data sets. - Ability to define metrics from scratch and build dashboards. - Experience with large‑scale A/B testing and experimentation. - Proven root‑cause analysis and process optimization skills. - Familiarity with both user‑facing product analytics and back‑end process improvements. - Data‑driven mindset with a track record of influencing product decisions. Required Education & Certifications: - Bachelor’s degree in Data Science, Statistics, Computer Science, Economics, or related field (equivalent experience may substitute). - No specific certifications required, but familiarity with data analytics tools (e.g., Python, R, Tableau, Looker) and fraud detection methodologies is advantageous.
London, United kingdom
On site
11-01-2026