Sr AI Machine Learning Engineer

The Hartford; Charlotte (NC); Hybrid; USD 117,200 - 175,800; Full time

Job summary

The Hartford is looking for a Senior Data Engineer to drive innovation in AI and machine learning. The role requires strong expertise in cloud services, specifically AWS and GCP, with an emphasis on building operational ML solutions. You will collaborate with various technical teams and mentor junior staff, ensuring the success of critical data projects.

This position offers a hybrid work schedule at locations including Charlotte, NC. The annual salary ranges from $117,200 to $175,800, based on experience and performance.

Qualifications

• Strong development experience in AWS, GCP or both.
• Experience in end-to-end model development lifecycle.
• Familiarity with emerging data-centric technologies.

Responsibilities

• Research and implement suitable ML algorithms and tools.
• Mentor junior engineers and provide technical guidance.
• Deploy ML models in AWS and GCP environments.

Skills

Generative and ML algorithms

Cloud services (AWS, GCP)

API services development

CI/CD pipelines

Python programming

Unix and Git

Education

Master’s degree or equivalent experience

Tools

Jenkins

Terraform

Apache Airflow

Job description

Sr Data Engineer - GE07BE

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.

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Global Specialty Applied AI team.

The Hartford is developing industry‑leading AI and machine learning capabilities to improve the various facets of the Global Specialty underwriting experience. On the Global Specialty Applied AI team, we utilize the latest AI products and frameworks to accelerate the processes that our partners touch day to day and advance the speed and intelligence with which we make our decisions. As a Senior Machine Learning AI Engineer, you will play a critical role in designing, building, and operationalizing production‑grade AI solutions—partnering closely with product, engineering, and platform leaders to deliver measurable impact.

Our core values

• We build AI solutions, not 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 our products 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 evolutional. We first deliver a minimally viable product and over time expand its sophistication based on feedback.

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 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.

Minimum 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.
• 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

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).

Candidates must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.

Compensation

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

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