Lead Machine Learning & AI Engineer

Overview

In this Lead ML/AI role, you will drive the design and delivery of production-ready ML and AI capabilities within our Data & Analytics function. You’ll mentor a small team of ML Ops, analytics, and AI engineers while partnering with Data Science, Pricing, Data Engineering and Software Development to embed AI across business processes. The role is hybrid and primarily home-based, with occasional office days. You’ll shape standards, advance data pipelines, and promote responsible, scalable AI solutions that support strategic decisions in insurance.

Pay / Benefits

• flexible hybrid work arrangement
• home-based with monthly office day
• career growth and leadership opportunities
• collaborative, high-impact environment

Responsibilities

• Develop and evolve ML/AI engineering standards and frameworks
• Enhance data pipelines and infrastructure for scaled ML/AI solutions
• Support model development with emphasis on auditability, versioning, and data security
• Design and implement AI Ops on Azure
• Optimize deployment of ML/AI scoring code in production
• Manage CI/CD and deployment/versioning of numerous models
• Monitor model quality and performance to prevent degradation
• Provide coaching and leadership to ML Ops/AI engineers and collaborate with data scientists, engineers, and software teams
• Engage with senior stakeholders to drive data-driven business improvements
• Lead system design discussions and share knowledge across the engineering community

Key requirements

• Extensive experience building end-to-end platform/ML DevOps/data engineering solutions
• Experience integrating cloud-based systems via APIs
• Proven track record in ML/AI system development and maintenance
• Experience with agile methods in data science/ML/AI settings
• Experience designing/managing CI/CD for data science
• Exposure to ML/AI methodologies and best practices
• Coaching/leadership experience
• Financial/insurance industry experience is advantageous
• Strong communication and organizational skills
• Ability to diagnose and troubleshoot quickly
• Bachelor’s or Master’s degree in a relevant field
• Fluent in Python; proficiency with PyTorch/TensorFlow
• Deep Azure expertise (Azure ML, Stream Analytics, Cognitive Services, Event Hubs, Synapse, Data Factory)
• Proficient in MLOps frameworks in production

• Excellent communication (verbal and written)
• Strong stakeholder management
• Self-motivated and proactive
• Python
• PyTorch
• TensorFlow

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