Sr. ML Ops Engineer

We are seeking a highly motivated Sr. ML Ops Engineer to join our team.

Our Client is one of the United States’ largest insurers, providing a wide range of insurance and financial services products with gross written premiums well over US$25 Billion (P&C). They proudly serve more than 10 million U.S. households with more than 19 million individual policies across all 50 states through the efforts of over 48,000 exclusive and independent agents and nearly 18,500 employees. Finally, our Client is part of one the largest Insurance Groups in the world.

The new ML Ops team will be our centralized shared services team supporting all ML Ops capabilities such as training, deployment, monitoring and feature stores. They will be responsible for the strategy and implementation of these capabilities as well as best practices for the business units to follow.

The Sr. ML Ops Engineer will support the ML Ops team and will work to build out the strategic ML Ops capabilities along with other engineers on the team. They will need to be proactive, own user stories, and follow engineering best practices from the team engineering

We count on you for :

• Delivering specific ML Ops engineering tasks such as moderate to complex level designing, developing, implementing, optimizing, and maintaining models, systems, and applications using existing and emerging technology platforms.
• Collaborating with cross-functional architecture teams to define and integrate frameworks and roadmaps for machine learning solutions, projects are generally of moderate complexity.
• Consulting on the design, development, and implementation of DevOps and ML Ops pipelines. May lead portions of deployment processes under guidance from people leader. Reviews, verifies, validates, and troubleshoots code to ensure high availability and high performance of machine learning models and applications.
• Using complex knowledge and understanding of code management principles and best practices to follow architectural and governance guidelines.
• Effectively communicating and applying machine learning engineering value, concepts, and strategies across multiple scenarios.

Requirements

Technical & Business Skills

Benefits

This position comes with a competitive compensation and benefits package.