Senior AI Machine Learning Engineer

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.
• Audit and promote MLOps best practices to the Data Science community.

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.
• 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 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.

Qualifications

• 4+ years of ML engineering, data manipulation and application development.
• 4+ years Python development experience.
• 4+ years working with IAC, developing CICD pipelines.
• 1+ years of experience in the insurance or broader financial services industry.
• 1+ years SQL development experience.
• Familiarity with emerging data centric technologies such generative AI, Agentic workflows, and embedding LLM’s into automated processes.

Pay

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is: $117,200 - $175,800.

Schedule

This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday).