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The Hartford Financial Services Group, Inc.

Machine Learning Engineer

Posted 21 Days Ago
4 Locations
101K-151K Annually
Mid level
4 Locations
101K-151K Annually
Mid level
The role involves building MLOps and Generative AI services, developing analytical tools, and managing model deployment pipelines in the cloud.
The summary above was generated by AI

Data Engineer - GE08AE

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’s Actuarial strategic modeling team is seeking a Machine Learning Engineer to build MLOps and Generative AI services. This role will be part of a dedicated hybrid actuarial/data science team designing and delivering powerful analytical tools utilizing statistical modeling, machine learning, cloud computing, and big data platforms to enhance or overhaul core actuarial processes. The individual will work closely with our data science and data engineering teams to develop training and deployment pipelines for core actuarial models.

This role is a Hybrid role that can be located in one of our four office locations (Hartford, CT, Charlotte, NC, Chicago, IL, and Columbus, OH).

Core Values:

  • Build AI/ML solutions, not just models.
  • Trusted and transparent collaboration.
  • Deliver safe, monitored products.
  • Earn influence through humble confidence.
  • Deliver viable products and evolve based on feedback.

Responsibilities:

  • Implement frameworks and technologies for AI/ML decision making.
  • Assess new data sources and techniques.
  • Development, and maintain of MLOps and GenAI platforms.
  • Deliver model deployment in AWS cloud.
  • Promote MLOps best practices.

Minimum Requirements:

  • Authorized to work in the U.S without sponsorship now or in the future.
  • Master’s degree or 2+ years of experience.
  • Experience with CICD pipelines and practices (GIT), Python, big data technologies (AWS/GCP/AZURE)
  • Experience in Cloud data warehouses (snowflake or equivalent), data pipelines and automation
  • General understanding of model development lifecycle and orchestration frameworks.

Preferred Skills:

  • Experience with AWS tools, SageMaker, Docker, and Agile frameworks.

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:

$100,960 - $151,440

Equal Opportunity Employer/Females/Minorities/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

About Us | Culture & Employee Insights | Diversity, Equity and Inclusion | Benefits

Top Skills

AWS
Azure
Big Data
Cloud Computing
GCP
Generative Ai
Machine Learning
Mlops
Python
Snowflake
Statistical Modeling

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