Senior AI Machine Learning Engineer

The Hartford

Confirmed live yesterday High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Hartford, CTCharlotte, NCColumbus, OHChicago, IL
Salary: $117,200–$175,800 / yr
Posted: 91 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $220k

This role $146k

$99k most similar roles pay here $283k

This role pays less than 92% of similar roles. Most pay $185,218–$254,750 — the shaded band above. At the midpoint, this role pays about $146k versus about $220k for comparable roles.

Based on 240 similar postings.

Employer

About The Hartford

The Hartford is a leading provider of property and casualty insurance, group benefits, and mutual funds, serving businesses and individuals across the United States. Industry: Insurance & Financial Services

The Hartford currently has 45 open roles on FindRole.

Listed pay typically runs $127,600–$191,400 across 37 roles with salary data.

Most-posted roles

View all roles at The Hartford

At a glance

TL;DR · Senior AI Machine Learning Engineer

Role Posting Log in to save

Sr AI Machine Learning Engineer will join the Global Specialty Applied AI team to build and operationalize production-grade machine learning solutions. This role focuses on developing MLOps services to enhance the global specialty underwriting experience by integrating advanced AI products and frameworks into daily workflows. The engineer is responsible for researching, experimenting with, and implementing generative and ML algorithms while managing the end-to-end model development lifecycle from ideation through post-production monitoring. Key responsibilities include designing deployment architectures, mentoring junior engineers, and promoting MLOps best practices. Technical requirements include proficiency in Python, Unix, and Git, along with experience in AWS or GCP environments. The candidate must demonstrate skills in building CI/CD pipelines using Jenkins, utilizing Infrastructure as Code tools like Terraform or CloudFormation, and working with workflow automation platforms such as Apache Airflow to automate complex processes.

Skills

MLOps Generative AI Python AWS GCP CICD Terraform Cloud Formation Apache Airflow Git Unix LLM Infrastructure as Code Machine Learning Agentic Workflows

What you'll do

Research, experiment with, and implement suitable Generative AI and machine learning algorithms.
Design, develop, and maintain production-grade traditional ML and AI models.
Build and deploy API services and model deployments within AWS and GCP cloud environments.
Implement MLOps best practices to support the data science community.
Develop repeatable architectural patterns to identify and eliminate system redundancies.
Create CI/CD pipelines and manage infrastructure using tools like Jenkins, Terraform, or CloudFormation.
Automate workflows using platforms such as Apache Airflow or Autosys.
Provide mentorship and technical leadership to junior engineers and peers.

What we're looking for

Master’s degree in a related field or 5+ years of experience in a research or DevOps function.
Experience developing solutions within AWS, GCP, or both.
Experience building and deploying API services within the cloud.
Experience building CI/CD pipelines using Jenkins or equivalent tools.
Experience with Infrastructure as Code (IaC) including CloudFormation, Terraform, or equivalents.
Proficiency in Unix, git, and strong object-oriented development experience using Python.
Experience in end-to-end model development lifecycle, workflow automation platforms, and emerging data-centric technologies like generative AI.
Authorized to work in the U.S. now and in the future.

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