Senior AI, Machine Learning Engineer

The Hartford

Senior AI Machine Learning Engineer building Machine Learning Operations services at The Hartford. Collaborating to design and operationalize AI solutions for customer experience improvement.

Posted 5/7/2026full-timeChicago • Connecticut, Illinois, North Carolina, Ohio • 🇺🇸 United StatesSenior💰 $137,200 - $205,800 per yearWebsite

Tech Stack

Tools & technologies

AirflowAmazon RedshiftApacheAWSBigQueryCloudGoogle Cloud PlatformHadoopJavaJenkinsPythonRDBMSSparkSQLTerraform

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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 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 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.

Benefits

Comp & perks

Short-term or annual bonuses
Long-term incentives
On-the-spot recognition

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Generative algorithmsMachine Learning algorithmsMLOps best practicesAWSGCPPythonJavaC#SQLInfrastructure as Code

Soft Skills

mentorshipthought leadershippresentation skillscollaborationaccountability

Certifications

Master’s degree