Sr Applied AI Machine Learning Engineer - Claims Data Science

The Hartford is a leading insurance company dedicated to making a difference by providing innovative solutions. They are seeking a Senior Applied AI Machine Learning Engineer to build MLOps services for the Claims Data Science team, focusing on delivering AI solutions that enhance decision-making in claims processes.

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 leadership and partners on an ongoing basis to calibrate deliverables against expectations
• Accountable for design, development and maintenance of Models as Service
• Work with junior engineers and peers to provide mentorship and thought leadership
• Be comfortable presenting new concepts to technical audiences
• Collaborate with partners Enterprise Data, Data Science, Business, Cloud Enablement Team, and Enterprise 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
• Proactively monitor cloud usage to drive cost-saving opportunities across cloud accounts and deployed infrastructure

Requirements:

• Master's degree in related field or 5+ years of equivalent experience in a research or DevOps function
• Development experience using the AWS suite of Tools, and ideally similar experience on GCP as well
• Familiarity with SageMaker, Streamlit, web security and encryption, credentials and API management tools
• Experience developing repeatable architectural patterns; ability to identify redundancies and eliminate them with these patterns
• Experience building and deploying webservices in a cloud environment
• Experience building CICD pipeline using Jenkins or equivalent
• Experience with IAC (Infrastructure as Code) including Cloud Formation, Terraform, or similar
• Expert-level Github experience, including Github Actions
• Strong object oriented development experience using Python, Java, C#
• Familiarity with big data technologies (i.e. Hadoop, Spark, Hive, etc.) and RDBMS platforms such as Redshift, Snowflake or BigQuery
• Experience in end to end model development lifecycle, from ideation through post production monitoring
• Experience with workflow automation platforms (Apache Airflow, Autosys, similar)
• Experience with Solution Design and Architecture of data pipelines
• Basic understanding of Data Science model development life cycle
• 4+ years of data engineering, data manipulation and application development
• 1+ years of experience in the insurance or broader financial services industry
• 4+ years SQL development experience
• 4+ years Python development experience
• 4+ years working with IAC, developing CICD pipelines
• Experience with emerging data-centric technologies such generative AI, Agentic workflows, and embedding LLM's into automated processes
• Candidate must be authorized to work in the US without company sponsorship
• Fundamentally strong with Data Structures and algorithms
• Experience working with Docker, Kubernetes and EC2 environment
• Experience building ML and data pipeline and orchestration services
• Basic understanding of ML frameworks i.e. Tensorflow, Anacoda, Scikit Learn, H20
• Experience working in an Agile framework