The Hartford
Sr Machine Learning Engineer – The Hartford
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Sr Machine Learning Engineer
role at
The Hartford .
Hybrid Work Schedule The role will have a hybrid work schedule. Expect to work 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 suitable frameworks, tools, and technologies to enable AI/ML decision‑making at scale.
Participate in identifying and assessing opportunities, such as the value of new data sources and analytical techniques, to ensure ongoing competitive advantage.
Review work with leadership and partners on an ongoing basis to calibrate deliverables against expectations.
Accountable for the ownership of design, development, and maintenance of MLOps and GenAI platforms and services.
Work with junior engineers and peers to provide mentorship and thought leadership.
Collaborate with partners Enterprise Data, Data Science, Business, Cloud Enablement Team, and Enterprise Architecture teams.
Delivery of critical milestones for model deployment in the Google Cloud Platform (GCP) and AWS cloud.
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 a related field and 5+ years of experience.
Solid understanding of the 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 and experience building orchestration framework for real‑time and batch model services.
Good understanding of various model development algorithms and types of ML use cases e.g., regression, classification, etc.
Strong fundamental knowledge of data structures and algorithms.
Preferred Skills
Development experience for WebService API with AWS suite of Tools.
Familiarity with big data technologies (i.e., Hadoop, Spark, Hive, etc.) and RDBMS.
Hands‑on experience with public cloud GCP, especially Vertex AI, Cloud Run, BigQuery, and GKE.
Basic understanding of ML frameworks i.e., Tensorflow, Scikit Learn, etc.
Experience with Agile framework and scrum/Kanban based project management.
Candidate Authorization Candidate must be authorized to work in the U.S. without company sponsorship. The company will not support the STEM OPT I‑983 Training Plan endorsement for this position.
Compensation The listed annualized base pay range is:
$117,200 - $175,800 . Actual base pay could vary based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role.
Equal Opportunity Employer Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age.
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Sr Machine Learning Engineer
role at
The Hartford .
Hybrid Work Schedule The role will have a hybrid work schedule. Expect to work 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 suitable frameworks, tools, and technologies to enable AI/ML decision‑making at scale.
Participate in identifying and assessing opportunities, such as the value of new data sources and analytical techniques, to ensure ongoing competitive advantage.
Review work with leadership and partners on an ongoing basis to calibrate deliverables against expectations.
Accountable for the ownership of design, development, and maintenance of MLOps and GenAI platforms and services.
Work with junior engineers and peers to provide mentorship and thought leadership.
Collaborate with partners Enterprise Data, Data Science, Business, Cloud Enablement Team, and Enterprise Architecture teams.
Delivery of critical milestones for model deployment in the Google Cloud Platform (GCP) and AWS cloud.
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 a related field and 5+ years of experience.
Solid understanding of the 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 and experience building orchestration framework for real‑time and batch model services.
Good understanding of various model development algorithms and types of ML use cases e.g., regression, classification, etc.
Strong fundamental knowledge of data structures and algorithms.
Preferred Skills
Development experience for WebService API with AWS suite of Tools.
Familiarity with big data technologies (i.e., Hadoop, Spark, Hive, etc.) and RDBMS.
Hands‑on experience with public cloud GCP, especially Vertex AI, Cloud Run, BigQuery, and GKE.
Basic understanding of ML frameworks i.e., Tensorflow, Scikit Learn, etc.
Experience with Agile framework and scrum/Kanban based project management.
Candidate Authorization Candidate must be authorized to work in the U.S. without company sponsorship. The company will not support the STEM OPT I‑983 Training Plan endorsement for this position.
Compensation The listed annualized base pay range is:
$117,200 - $175,800 . Actual base pay could vary based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role.
Equal Opportunity Employer Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age.
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