Senior Applied AI Machine Learning Engineer – Claims Data Science
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Job Description
Senior Applied AI Machine Learning Engineer developing MLOps services for Claims Data Science team at The Hartford. Building AI solutions for smarter decision making in claims processes.
Responsibilities:
- Research, experiment with, and implement suitable Generative and ML algorithms, tools and technologies.
- Participate in identifying and assessing opportunities i.e. value of new data sources and analytical techniques and technology, to ensure ongoing competitive advantage.
- Review work with leadership and partners on an ongoing basis to calibrate deliverables against expectations.
- Accountable for design, development and maintenance of Models as Service
- Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable presenting new concepts to technical audiences.
- Collaborate with partners Enterprise Data, Data Science, Business, Cloud Enablement Team, and Enterprise Architecture teams
- Delivery of critical milestones for model deployment in the AWS and GCP clouds.
- Adopt and promote MLOps best practices to the Data Science community.
- Proactively monitor cloud usage to drive cost-saving opportunities across cloud accounts and deployed infrastructure.
Requirements:
- Master’s degree in related field or 5+ years of equivalent experience in a research or DevOps function
- Development experience using the AWS suite of Tools, and ideally similar experience on GCP as well
- Familiarity with SageMaker, Streamlit , web security and encryption, credentials and API management tools
- Experience developing repeatable architectural patterns; ability to identify redundancies and eliminate them with these patterns.
- Experience building and deploying webservices in a cloud environment.
- Experience building CICD pipeline using Jenkins or equivalent
- Experience with IAC (Infrastructure as Code) including Cloud Formation, Terraform, or similar
- Expert-level Github experience, including Github Actions
- Strong object oriented development experience using Python, Java, C#
- Familiarity with big data technologies (i.e. Hadoop, Spark, Hive, etc.) and RDBMS platforms such as Redshift, Snowflake or BigQuery
- Experience in end to end model development lifecycle, from ideation through post production monitoring.
- Experience with workflow automation platforms (Apache Airflow, Autosys, similar)
- Experience with Solution Design and Architecture of data pipelines
- Basic understanding of Data Science model development life cycle
Benefits:
- Other rewards may include short-term or annual bonuses
- Long-term incentives
- On-the-spot recognition
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