Principal Machine Learning Engineer (AI)

TL;DR

Principal Machine Learning Engineer (AI): Leading the architectural strategy and development of production-grade ML systems and MLOps platforms with an accent on scalability, reliability, and operational excellence. Focus on bridging the gap between experimentation and production, mentoring engineering teams, and establishing best practices for AI-assisted development within a complex insurance environment.

Location: Must be based in or able to work from London or York

Company

A global specialist insurer tackling complex risks through deep expertise and sophisticated data and machine learning capabilities.

What you will do

• Lead the technical direction for complex, business-critical ML systems from design to production.
• Define and evolve MLOps patterns, including deployment, orchestration, monitoring, and lifecycle management.
• Partner with platform teams to build and scale the ML infrastructure and CI/CD pipelines.
• Provide hands-on technical mentorship to ML engineers and data scientists to raise engineering standards.
• Establish guardrails and best practices for the responsible use of AI-assisted coding tools.
• Ensure ML systems meet high standards for security, compliance, and operational reliability.

Requirements

• Must be based in or able to work from London or York
• Extensive experience as a senior or principal ML engineer delivering production systems at scale.
• Exceptional Python skills with strong software engineering fundamentals.
• Deep expertise in MLOps, CI/CD, and infrastructure as code (e.g., Terraform).
• Hands-on experience with major cloud platforms (AWS, GCP, or Azure) and containerized deployments.
• Strong operational mindset with experience in monitoring, observability, and incident response.

Nice to have

• Experience in the insurance or financial services industry.
• Proven track record of shaping ML platforms or critical ML infrastructure.

Culture & Benefits

• Opportunity to influence strategic AI adoption across the London Market.
• Culture that values technical excellence, ownership, and courage.
• Autonomy to set standards and explore emerging technologies.
• Collaborative environment with a focus on long-term system sustainability.