Sr Machine Learning Engineer

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Overview Sr Data Engineer - GE07BE The Hartford’s Personal Lines Data Analytics team seeks an energetic and passionate Senior Machine Learning Engineer to help build and scale our next-generation machine learning operations (MLOps) and Generative AI (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 the expectation of working in an office (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 the value of new data sources and analytical techniques, to ensure ongoing competitive advantage. Review work with leadership and partners to calibrate deliverables against 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 Team, 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 the development of 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 and techniques 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. Good understanding of 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 fundamental knowledge of data structures and algorithms.
Preferred Skills
Development experience for WebService API with AWS tools. Familiarity with big data technologies (Hadoop, Spark, Hive) and RDBMS. Hands-on experience with GCP, especially Vertex AI, Cloud Run, BigQuery, and GKE. Basic understanding of ML frameworks (TensorFlow, scikit-learn). Experience with Agile frameworks (Scrum/Kanban).
Compensation The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary based on factors such as performance and competencies. The base pay is one component of The Hartford’s total compensation package, which may include bonuses and other rewards. 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 Employment type
Full-time
Seniority level
Mid-Senior level
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Location:
Chicago, IL, United States
Job Type:
FullTime

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