ML Engineering Manager — Lead Real-Time AI Systems

Compare the Market; Greater London; Hybrid; GBP 110,000 - 140,000; Full time

Job summary

Compare the Market, a data-driven financial decision platform, seeks a Machine Learning Engineering Manager to lead production ML/AI systems from London in a hybrid setup. You will own technical direction, mentor engineers, and partner with data, product, and commercial teams to drive high-impact ML outcomes.

You will set standards for ML tooling, deployment, monitoring, and governance while guiding the team through a fast-moving AI landscape and ensuring responsible, auditable AI practices

Qualifications

• Experience leading engineering teams focused on machine learning, ML platforms and AI systems.
• Proven track record deploying and managing ML/AI systems in production at scale (real-time inference, batch data products, LLM-based solutions).
• Strong Python and ML engineering fundamentals with ability to contribute directly when needed.
• Understanding of infrastructure-as-code and CI/CD for ML systems (e.g. Terraform, GitHub Actions, ArgoCD).

Responsibilities

• Lead and develop a team of ML engineers, delivering robust, scalable systems into production (real-time APIs, batch data products, LLM-based solutions).
• Collaborate with data scientists to move prototypes into production with quality and performance as complexity scales.
• Drive team planning, estimation, and sprint delivery to meet deadlines and standards.
• Ensure every system ships connects to real outcomes and has measurement to improve over time.

Skills

Leadership

Python

Communication

Agile

CI/CD

Education

Degree in quantitative discipline

Tools

Terraform

GitHub Actions

ArgoCD

LangGraph

LangChain

Job description

Compare the Market, a data-driven financial decision platform, seeks a Machine Learning Engineering Manager to lead production ML/AI systems from London in a hybrid setup. You will own technical direction, mentor engineers, and partner with data, product, and commercial teams to drive high-impact ML outcomes.

You will set standards for ML tooling, deployment, monitoring, and governance while guiding the team through a fast-moving AI landscape and ensuring responsible, auditable AI practices