AI Machine Learning Engineer

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.

We build AI solutions, not just 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 products are delivered with a full monitoring solution to ensure they 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 evolutionary. We first deliver a minimally viable product and over time expand its sophistication based on feedback.

• Research, experiment with, and implement suitable Generative AI 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.
• Deliver critical milestones for model deployment in the AWS and GCP clouds.
• Adopt and promote MLOps best practices to the Data Science community.

• Must be authorized to work in the U.S. now and in the future.
• Bachelor’s degree in a related field or 7+ years of equivalent experience in Research, Engineering, Data Science, or Dev Ops.
• Development experience building 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 with CI/CD pipelines.
• 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 the Data Science model development life cycle.
• Familiarity with emerging data‑centric technologies such as generative AI, agentic workflows, and embedding LLMs into automated processes.
• Candidate must be authorized to work in the U.S. without company sponsorship. The company will not support the STEM OPT I‑983 Training Plan endorsement for this position.

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.

Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age