Senior AI Machine Learning Engineer

Sr Cloud Engineer - IE07NE We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future. The Hartford seeks a driven, team-focused Senior AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Customer Operations Data Science team. The Hartford is developing industry‑leading AI and machine learning capabilities to improve customer experience (CX) at scale. Within Customer Operations Data Science, we build modern AI products that optimize customer interactions across omnichannel journeys, supporting operational areas such as the Contact Center, Premium Audit, and Billing. As a Senior Machine Learning Engineer, you will play a critical role in designing, building, and operationalizing production‑grade AI solutions—partnering closely with product, engineering, and operations leaders to deliver measurable impact. Our core values We build AI solutions, not models. We are thoughtful in supporting the end-to-end business problem, with an eye to systems design. We are trusted and transparent. We collaborate tightly with our partners and are mindful of their capacity to absorb change. We provide assets that are safe to buy. Our pr [... source excerpt omitted ...] ull monitoring solution to ensure our products continue to deliver as expected. We will earn the right to influence. With humble confidence, we listen carefully to learn from our customers and become partners in problem solving. We are practical and evolutional. We first deliver a minimally viable product and over time expand its sophistication based on feedback. Responsibilities Research, experiment with, and implement suitable Generative and ML algorithms, tools and technologies. Participate in identifying and assessing opportunities i.e. value of new data sources and analytical techniques and technology, to ensure ongoing competitive advantage. Review work with leadershi [... source excerpt omitted ...] Architecture teams Delivery of critical milestones for model deployment in the AWS and GCP clouds. Adopt and promote MLOps best practices to the Data Science community. Minimum Requirements Must be authorized to work in the U.S. now and in the future. Master’s degree in related field or 5+ years of equivalent experience in a research or DevOps function. Development experience using both the AWS and GCP suite of tools. Familiarity with SageMaker, Streamlit, web security, credentials and API management tools Experience developing repeatable architectural patterns; ability to identify redundancies and eliminate them with these patterns. Experience building and deploying webserv