The Hartford
Overview
Join to apply for the
Sr Machine Learning Engineer
role at
The Hartford . The Hartford’s Personal Lines Data Analytics team seeks energetic and passionate Senior Machine Learning Engineer to help build and scale our next-generation Machine Learning Operations (MLOps) & GenAI platforms. This role blends software engineering, DevOps, and machine learning expertise to deliver robust, scalable, and secure AI/ML solutions. You will be instrumental in enabling our data science teams to deploy models efficiently and responsibly in production environments. We are looking for talent who embraces our core values: We build artificial intelligence/machine learning solutions, not models. We support end-to-end business problems with a focus on systems design. We are trusted and transparent, collaborating closely with our partners and considering their capacity for change. Our products are delivered with full monitoring solutions to ensure they continue to perform as expected. We listen carefully to our customers and become partners in problem-solving with humble confidence. We deliver minimally viable products first and expand their sophistication over time based on feedback. This role will have a hybrid work schedule with a preference for in-office presence in Columbus, OH; Chicago, IL; Hartford, CT; or Charlotte, NC 3 days a week (Tuesday through Thursday).
Responsibilities
Research, experiment with, and implement frameworks, tools, and technologies to enable AI/ML decision-making at scale. Identify and assess opportunities, such as new data sources and analytical techniques, to maintain competitive advantage. Review work with leadership and partners to calibrate deliverables against expectations. Own design, development, and maintenance of MLOps and GenAI platforms and services. Mentor junior engineers and provide thought leadership. Collaborate with Enterprise Data, Data Science, Business, Cloud Enablement, and Enterprise Architecture teams. Deliver critical milestones for model deployment in Google Cloud Platform (GCP) and AWS. Develop, adopt, and promote MLOps best practices to the data science community. Implement infrastructure-as-code using Terraform or CloudFormation to automate deployments. Contribute to agentic AI capabilities and support experimentation with LLMs and GenAI frameworks.
Requirements
Must be authorized to work in the U.S. now and in the future. Bachelor's degree in related field and 5+ years of experience. Solid understanding of ML lifecycle: model training, deployment, monitoring, and feedback loops. Strong application development experience using Python. 3+ years of hands-on experience developing with one of the public clouds including tools to auto-scale systems. Experience with CI/CD and IAC tools (e.g., Terraform, Jenkins, GitHub Actions) and containerization (Docker, Kubernetes). Good understanding of Generative AI technologies, frameworks, key LLMs, and architecture patterns. Exposure to agentic AI architectures and prompt engineering. Experience building orchestration frameworks for real-time and batch model services. Good understanding of various model development algorithms and ML use cases (e.g., regression, classification). Strong fundamentals in data structures and algorithms.
Preferred Skills
WebService API development with AWS tools. Familiarity with big data technologies (Hadoop, Spark, Hive) and RDBMS. Hands-on experience with GCP, Vertex AI, Cloud Run, BigQuery, and GKE. Basic understanding of ML frameworks (TensorFlow, Scikit-Learn). Experience with Agile, Scrum/Kanban project management.
Compensation
The listed annualized base pay range is based on external market analysis. Base pay may vary based on performance, proficiency, and competencies. The base pay is part of The Hartford’s total compensation package. Other rewards may include bonuses, incentives, and recognition. The annualized base pay range for this role is: $117,200 - $175,800
Equal Opportunity
Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
About Us
About Us | Our Culture | What It’s Like to Work Here | Perks & Benefits
#J-18808-Ljbffr
Join to apply for the
Sr Machine Learning Engineer
role at
The Hartford . The Hartford’s Personal Lines Data Analytics team seeks energetic and passionate Senior Machine Learning Engineer to help build and scale our next-generation Machine Learning Operations (MLOps) & GenAI platforms. This role blends software engineering, DevOps, and machine learning expertise to deliver robust, scalable, and secure AI/ML solutions. You will be instrumental in enabling our data science teams to deploy models efficiently and responsibly in production environments. We are looking for talent who embraces our core values: We build artificial intelligence/machine learning solutions, not models. We support end-to-end business problems with a focus on systems design. We are trusted and transparent, collaborating closely with our partners and considering their capacity for change. Our products are delivered with full monitoring solutions to ensure they continue to perform as expected. We listen carefully to our customers and become partners in problem-solving with humble confidence. We deliver minimally viable products first and expand their sophistication over time based on feedback. This role will have a hybrid work schedule with a preference for in-office presence in Columbus, OH; Chicago, IL; Hartford, CT; or Charlotte, NC 3 days a week (Tuesday through Thursday).
Responsibilities
Research, experiment with, and implement frameworks, tools, and technologies to enable AI/ML decision-making at scale. Identify and assess opportunities, such as new data sources and analytical techniques, to maintain competitive advantage. Review work with leadership and partners to calibrate deliverables against expectations. Own design, development, and maintenance of MLOps and GenAI platforms and services. Mentor junior engineers and provide thought leadership. Collaborate with Enterprise Data, Data Science, Business, Cloud Enablement, and Enterprise Architecture teams. Deliver critical milestones for model deployment in Google Cloud Platform (GCP) and AWS. Develop, adopt, and promote MLOps best practices to the data science community. Implement infrastructure-as-code using Terraform or CloudFormation to automate deployments. Contribute to agentic AI capabilities and support experimentation with LLMs and GenAI frameworks.
Requirements
Must be authorized to work in the U.S. now and in the future. Bachelor's degree in related field and 5+ years of experience. Solid understanding of ML lifecycle: model training, deployment, monitoring, and feedback loops. Strong application development experience using Python. 3+ years of hands-on experience developing with one of the public clouds including tools to auto-scale systems. Experience with CI/CD and IAC tools (e.g., Terraform, Jenkins, GitHub Actions) and containerization (Docker, Kubernetes). Good understanding of Generative AI technologies, frameworks, key LLMs, and architecture patterns. Exposure to agentic AI architectures and prompt engineering. Experience building orchestration frameworks for real-time and batch model services. Good understanding of various model development algorithms and ML use cases (e.g., regression, classification). Strong fundamentals in data structures and algorithms.
Preferred Skills
WebService API development with AWS tools. Familiarity with big data technologies (Hadoop, Spark, Hive) and RDBMS. Hands-on experience with GCP, Vertex AI, Cloud Run, BigQuery, and GKE. Basic understanding of ML frameworks (TensorFlow, Scikit-Learn). Experience with Agile, Scrum/Kanban project management.
Compensation
The listed annualized base pay range is based on external market analysis. Base pay may vary based on performance, proficiency, and competencies. The base pay is part of The Hartford’s total compensation package. Other rewards may include bonuses, incentives, and recognition. The annualized base pay range for this role is: $117,200 - $175,800
Equal Opportunity
Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
About Us
About Us | Our Culture | What It’s Like to Work Here | Perks & Benefits
#J-18808-Ljbffr