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.
Minimum Requirements
Development experience using both the AWS and GCP suite of tools.
Familiarity with SageMaker, Streamlit, web security, 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
Preferred Skills
Fundamentally strong with Data Structures and algorithms.
Experience working with Docker, Kubernetes and EC2 environment.
Experience building ML and data pipeline and orchestration services
Basic understanding of ML frameworks i.e. Tensorflow, Anacoda, Scikit Learn,
Experience working in an Agile framework.
Requirements
ML engineering, data manipulation and application development
Python development experience
Working with IAC, developing CICD pipelines
Experience in the insurance or broader financial services industry
SQL development experience
Familiarity with emerging data centric technologies such generative AI, Agentic workflows, and embedding LLM's into automated processes
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Additional Information
IND Staff Engineer - GCC094
We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future.
Thehartford · Gcc-puppalaguda Village, India