Join to apply for the Sr Machine Learning Engineer role at The Hartford .

Skills, Experience, Qualifications, If you have the right match for this opportunity, then make sure to apply today. The Hartford’s Personal Lines Data Analytics team is seeking an energetic and passionate Senior Machine Learning Engineer to help build and scale our next-generation Machine Learning Operations (MLOps) & Generative AI (GenAI) platforms. This role combines software engineering, DevOps, and machine learning expertise to deliver robust, scalable, and secure AI/ML solutions. You will enable our data science teams to deploy models efficiently and responsibly in production environments. We value candidates who embrace our core principles: Building AI/ML solutions that address end-to-end business problems with a focus on systems design. Being trusted and transparent, collaborating closely with partners and considering their capacity for change. Delivering products with full monitoring solutions to ensure ongoing performance. Listening carefully to customers and partnering with humility and confidence. Delivering minimally viable products first, then expanding their capabilities based on feedback. This role offers a hybrid schedule, requiring in-office work in Columbus, OH, Chicago, IL, Hartford, CT, or Charlotte, NC, three 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 align deliverables with expectations. Own the 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 Architecture teams. Deliver critical milestones for model deployment on Google Cloud Platform (GCP) and AWS. Promote MLOps best practices within the Data Science community. Implement infrastructure-as-code using Terraform or CloudFormation for automation. Support experimentation with LLMs and GenAI frameworks, contributing to agentic AI capabilities. Requirements Authorized to work in the U.S. now and in the future. Bachelor’s degree in a related field and 5+ years of experience. Strong understanding of the ML lifecycle: training, deployment, monitoring, and feedback. Proficiency in Python application development. 3+ years of hands-on experience with public clouds, including auto-scaling tools and techniques. Experience with CI/CD, IAC tools (e.g., Terraform, Jenkins, GitHub Actions), and containerization (Docker, Kubernetes). Good understanding of Generative AI technologies, frameworks, and architecture patterns. Familiarity with agentic AI architectures and prompt engineering. Experience building orchestration frameworks for real-time and batch model services. Knowledge of ML algorithms and use cases such as regression and classification. Fundamental data structures and algorithms knowledge. Preferred Skills Web service API development with AWS tools. Experience with big data technologies (Hadoop, Spark, Hive) and RDBMS. Hands-on experience with GCP, especially Vertex AI, Cloud Run, BigQuery, and GKE. Basic knowledge of ML frameworks like TensorFlow and Scikit-Learn. Experience with Agile and Scrum/Kanban project management. Compensation The annual base pay ranges from $117,200 to $175,800, based on market analysis and individual factors. Compensation includes bonuses, incentives, and other rewards. Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age. Additional Information Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and IT

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