At a Glance
- Tasks: Build and maintain data pipelines and ML solutions while collaborating with product teams.
- Company: Join a fast-growing fintech unicorn on a mission to change money management.
- Benefits: Competitive pay, equity options, flexible work, and generous leave policies.
- Other info: Enjoy regular socials, online mental health support, and a clear progression plan.
- Why this job: Make a real impact in a turbo-charged startup with a collaborative culture.
- Qualifications: Experience in data engineering, Python, and cross-functional collaboration.
The predicted salary is between 63000 - 77000 £ per year.
About Cleo
We are a fast‑growing fintech unicorn on a mission to fundamentally change how people manage their money.
With over $300 million ARR and 2x Yo Y growth, we combine a hyper‑intelligent financial advisor with a passionate, collaborative culture.
Join a team of brilliant, driven individuals who push complex challenges, shape transformative products, and share in our success.
Position Overview
Support our product teams in achieving their OKRs by championing best practices in data engineering and MLOps.
Work closely with product units to adopt tools, frameworks, and processes from the Data Platform team.
Build scalable, efficient, and reliable data‑and‑ML solutions while acting as a bridge between product and platform to surface real‑world pain points and drive continuous improvement.
Responsibilities
- Build and maintain robust data pipelines, model deployment workflows, monitoring strategies, and cost‑efficient practices.
- Serve as a liaison between product teams and the Data Platform team, gathering insights on challenges, gaps, and pain points.
- Collaborate with engineers, data scientists, and product managers to align ML initiatives with business goals.
- Contribute to both hands‑on engineering delivery and strategic platform evolution.
Qualifications
- Experience designing data systems and breaking down work.
- Solid experience with data engineering languages (Python preferred).
- Knowledge of at least one distributed processing framework (e. g., Py Spark, Flink). Streaming experience a plus.
- Containerisation & orchestration (Docker, Kubernetes).
- Infrastructure as Code (Terraform).
- Software engineering best practices, code quality, and maintainability.
- Understanding of different storage types (OLTP, OLAP, S3) and their appropriate use.
- Product thinking and value‑centric mindset.
- Cross‑functional collaboration with data scientists, engineers, and product managers.
- Nice to Haves
- Experience running a streaming platform and knowledge of stream‑to‑table and table‑to‑stream transformations.
- Deep technical knowledge of core data structures and distributed processing with a focus on practical application.
- Monitoring and alerting expertise for data systems.
- Experience deploying APIs and systems outside of the core data platform.
- Experience with Feature Stores and building/managing ML pipelines (Kubeflow, MLflow, Airflow, Flyte).
- Tech Stack
Ruby on Rails monolith with a React Native/Type Script frontend, Python for ML services, Postgre SQL on AWS.
CI/CD is fully automated with production deployments on merge via Heroku, and frequent frontend releases to Google Play and the Apple Store.
Benefits
- Competitive compensation (base + equity) with bi‑annual reviews aligned to OKR cycles.
- Opportunity to work at a turbo‑charged startup backed by top VC firms.
- Clear progression plan and ownership culture.
- Flexibility in working location and schedule.
- Global team with remote Polish office and virtual socials; annual offsite in Europe.
- Company‑wide performance reviews every 6 months.
- Generous pay increases for high performers.
- Equity top‑ups upon promotion.
- 25 days annual leave + public holidays, plus extra day per year at Cleo up to 30 days.
- Private medical insurance (Alan).
- 1 month paid sabbatical after 4 years.
- Regular socials and activities, online and in‑person.
- Open AI subscription paid by the company.
- Online mental health support via Spill.
Compensation
- Poland: PLN 1‑1.0 M gross annually*
- Other locations: Compensation discussed during the interview process.
- Final pay determined by qualifications, skills, and prior experience.
- Equal Opportunity
We strongly encourage applications from people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers, and people from lower socio‑economic backgrounds.
If there’s anything we can do to accommodate your specific situation, please let us know.
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Lead MLOps Engineer employer: cleo
Cleo is an exceptional employer that prioritises the financial health of its users while fostering a collaborative and innovative work culture. With flexible hybrid working options and a competitive salary, employees are encouraged to grow through mentorship and cross-functional teamwork, making it a rewarding place for those passionate about machine learning and impactful solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Lead MLOps Engineer
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Lead MLOps Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at cleo. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at cleo
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at cleo!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.