Senior AI Machine Learning Engineer

The Hartford

Senior AI Machine Learning Engineer focusing on MLOps services for The Hartford's Global Specialty Applied AI team. Partnering for impactful AI solutions and managing production-grade deployments.

Posted 6/14/2026full-timeHartford • Connecticut, Illinois, North Carolina, Ohio • 🇺🇸 United StatesSenior💰 $117,200 - $175,800 per yearWebsite

Tech Stack

Tools & technologies

AirflowApacheAWSCloudGoogle Cloud PlatformJenkinsPythonTerraformUnix

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 deployment design, development and maintenance of both traditional ML and AI models.
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, Applied AI, 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

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 developing solutions within AWS, GCP or both.
Experience developing repeatable architectural patterns; ability to identify redundancies and eliminate them with these patterns.
Experience building and deploying API services within the Cloud.
Experience building CICD pipeline using Jenkins or equivalent
Experience with IAC (Infrastructure as Code) including Cloud Formation, Terraform, or equivalents
Experience in Unix, git, and strong object oriented development experience using Python
Experience in end to end model development lifecycle, from ideation through post production monitoring.
Experience with workflow automation platforms (Apache Airflow, Autosys, similar)
Basic understanding of Data Science model development life cycle
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 algorithmsMLOpsAPI servicesCICD pipelineInfrastructure as CodePythonUnixCloud FormationTerraform

Soft Skills

mentorshipthought leadershippresentation skillscollaboration