Lead MLOps Engineer

Cleo; Greater London; On-site; GBP 60,000 - 100,000; Full time

Benefits offered by this job

Competitive compensation (base + equity)

Clear progression plan and ownership culture

25 days annual leave + public holidays

Job summary

Cleo in Greater London is seeking a data engineering expert to support product teams in achieving their objectives while advocating for best practices in MLOps. Your role will involve building scalable data and ML solutions and serving as a bridge between product development and platform operations.

The ideal candidate will possess strong skills in data engineering, particularly in Python, and experience with distributed processing. The position offers a flexible working environment, competitive compensation, and a collaborative culture at a fast-growing fintech unicorn.

Qualifications

• Experience designing data systems and breaking down work.
• Solid experience with data engineering languages, preferably Python.
• Knowledge of distributed processing frameworks, like PySpark or Flink.

Responsibilities

• Build and maintain robust data pipelines and monitoring strategies.
• Liaise between product teams and the Data Platform team.
• Align ML initiatives with business goals.

Skills

Data engineering languages (Python preferred)

Distributed processing framework knowledge (e.g., PySpark, Flink)

Containerisation & orchestration (Docker, Kubernetes)

Infrastructure as Code (Terraform)

Product thinking

Cross-functional collaboration

Tools

PostgreSQL

Heroku

Job description

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 YoY 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., PySpark, 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/TypeScript frontend, Python for ML services, PostgreSQL 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.
• OpenAI 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.