FinTech MLOps Engineer

Overview

This stealth UK FinTech is using AI to transform how credit scoring works. They’ve developed proprietary models that are already proving their value — now they need an MLOps engineer to build the infrastructure that takes them to scale. You’ll own the full ML lifecycle: pipelines, deployment, monitoring, and continuous improvement. This is FinTech, so reliability and compliance aren’t optional — the systems you build will power real financial decisions for real people. The team is small and moves fast. They care deeply about attitude: they want someone who sees problems, makes a plan, and acts. No waiting around for permission. If you thrive on ownership and want to be part of something from the ground up, this is it.

Responsibilities

• Design and maintain ML pipelines for training, validation, and deployment
• Build robust model monitoring and observability — detecting drift, degradation, and anomalies before they become problems
• Implement feature stores and data pipelines that serve real‑time and batch inference
• Own the CI/CD for ML models — automated testing, canary deployments, and rollback strategies
• Ensure compliance and auditability of model decisions in a regulated environment
• Collaborate with data scientists to move models from notebooks to production

Qualifications

• 3+ years experience in FinTech or financial services — you understand the domain
• Strong experience with ML infrastructure — you’ve deployed and operated models in production
• Comfortable with Python and the modern ML tooling ecosystem (MLflow, Kubeflow, Airflow, or similar)
• Deep understanding of containerization and orchestration (Docker, Kubernetes)
• Experience with cloud platforms (AWS, GCP, or Azure) and infrastructure‑as‑code
• The right attitude — you see problems, you plan, you act. No hand‑holding required

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