Lead MLOps Engineer

Cleo; Greater London; On-site; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Equity

Health insurance

Pension

Learning and development platform

Job summary

Cleo is hiring an engineer to sit between product teams and the Data Platform, helping scale data and ML solutions. You will contribute to data pipelines, model deployment, and monitoring while aligning with business goals.

In this role you will collaborate with data scientists, software engineers, and product managers to drive impact and improve internal tooling, with a focus on robust, scalable data infrastructure.

Qualifications

• Ability to design data systems and break down work effectively.
• Strong Python development skills with focus on data engineering.
• Hands-on experience with distributed processing frameworks, preferably PySpark or Flink.

Responsibilities

• Bridge product teams and Data Platform to adopt tools and pipelines.
• Champion robust data pipelines, model deployment workflows, monitoring, and cost efficiency.
• Identify gaps and surface real-world challenges to improve the data platform.

Skills

Data system design

Python

Distributed processing

Cross-functional collaboration

ML initiatives

Tools

Docker

Kubernetes

Terraform

PySpark

Python (coding)

Job description

Most money apps talk at you. Cleo talks back

We're not building another finance app. We're building the world's first AI financial assistant, one that actually understands your money and makes you better at it, and we're changing the world's relationship with money in the process For everyone, whatever their background or balance.

The proof: profitable, fast-growing, a unicorn with over $300M in ARR, and millions of people who now feel differently about their money.

We love original thinkers who challenge the status quo. We move fast, tell the truth, and there's nowhere to hide from good work here. If that excites you more than it scares you, you'll fit right in.

Follow us on LinkedIn for new features and the occasional roast

Meet the team

Here at Cleo, we have ~200 Engineers organised into Pillars. Our stack spans a Ruby on Rails monolith, a single React Native (TypeScript) app frontend, Python for machine learning services, and PostgreSQL, all hosted on AWS and shipped through Kubernetes - backend goes out multiple times a week, app releases to Google and Apple at least weekly. To thrive here, our engineers proactively use our Engineering Principles to guide daily decisions, take ownership of problems beyond their own squad to drive broader impact, and actively drive their own learning, development, and growth.

About the role

We're hiring an engineer to sit between our product teams and the Data Platform team, helping product teams adopt the Data Platform's tools, frameworks, and processes so they can build scalable, efficient, and reliable data and ML solutions.

• Support product teams in achieving their OKRs while championing best practices in data engineering and MLOps
• Help teams implement robust data pipelines, model deployment workflows, monitoring strategies, and cost-efficient practices
• Act as the bridge between product teams and the Data Platform team, surfacing real-world challenges, gaps, and pain points in the existing platform
• Collaborate with the platform team to continuously improve internal tooling and infrastructure for engineers and data scientists
• Blend hands-on engineering with strategic impact, influencing both product success and the evolution of the data platform

What we're looking for

• Data system design and the ability to break down work
• Solid experience with a data engineering language (Python ideal)
• Knowledge of at least one distributed processing framework, ideally streaming (e.g. PySpark, Flink)
• Containerisation and orchestration - Docker, Kubernetes
• Infrastructure as Code - Terraform
• Software engineering best practices - proficiency in Python (preferred), code quality and maintainability
• Good knowledge of different storage types and when to use them - OLTP, OLAP, S3
• Understanding of value and product thinking
• Experience working cross-functionally with data scientists, software engineers, and product managers to align ML initiatives with business goals
• Nice to have: experience running streaming platforms and knowledge of stream-to-table and table-to-stream
• Nice to have: deep technical knowledge of core data structures and distributed processing, with a preference for practical application over theory
• Nice to have: monitoring and alerting as it pertains to data systems
• Nice to have: deploying APIs and systems outside of the core data platform, moving toward deploying ML systems
• Nice to have: experience working with feature stores
• Nice to have: experience building and managing ML pipelines (e.g. Kubeflow, MLflow, Airflow, Flyte)

What we offer

We offer benefits package built to support you in and out of work. Benefits vary by country and include meaningful equity, comprehensive health, dental and vision insurance, mental health support, a paid one-month sabbatical after four years, a learning and development platform, pension or retirement contributions, and location-specific leave entitlements. For the full breakdown on what's available in your location, visit our Candidate Hub

What Matters

Cleo's mission is to change the world's relationship with money. We can't do that without building a brilliant, genuinely diverse team - and making sure our hiring process gives everyone a fair shot, running a fair and transparent recruitment process in which every candidate is considered on their metris.

We're glad to make reasonable adjustments at any stage of the process. If there's anything we can do to support you in showing us your best, please let your recruiter or one of the team know.

We may use AI-assisted tools during the recruitment process to take support the team in different ways like taking notes or referring back to conversations. They do not replace the team and all applications are reviewed by a Cleo employee thoroughly!