Sr Machine Learning Engineer

$100,500 - $182,700/Yr

Blue Cross Blue Shield

Full-time - Mid Level

Insurance Carriers and Related Activities

About the position

Blue Cross and Blue Shield of North Carolina has an immediate need for a Senior Machine Learning Engineer. The ML engineering team plays an integral part in delivering on the enterprise's Data Science MLOps strategy and capabilities. Our ML Engineers will work closely with all Data Scientists to ensure AI/ML models are automated, whether traditional data science, machine learning, or generative AI. This role will be key in GenAI automation on the AWS ecosystem. The AI/ML COE builds foundational AI/ML capabilities and solutions that serve multiple cross-domain business use cases and provide thought-leadership on the potential of AI/ML in delivering transformational value for the enterprise. AI/ML COE maintains and matures our AI/ML operations environment, and AI/ML standards & best practices to enable scaling of data science solutions from ideation to prototype, automation, productionization, and integration into business workflows. AI/ML COE also maintains a community of practice for data scientists at BCBSNC and developing partnerships with universities, and other Blues plans. In this role, you will define and extract data from multiple sources, integrate disparate data into a common data model, and integrate data into a target database, application, or file using efficient programming processes. You will document and test complex data systems that bring together data from disparate sources, making it available to data scientists and other users using scripting and/or programming languages. Additionally, you will improve, deploy, and maintain models prepared by Data Scientists into production-grade cloud systems using scalable, efficient machine learning operations pipelines. Your responsibilities will also include writing and refining code to ensure performance and reliability of data extraction and processing, leading requirements gathering sessions with business and technical staff, and developing advanced SQL queries to extract data for analysis and model construction.

Responsibilities

• Define and extract data from multiple sources, integrate disparate data into a common data model, and integrate data into a target database, application, or file using efficient programming processes.
• Document, and test complex data systems that bring together data from disparate sources, making it available to data scientists and other users using scripting and/or programming languages.
• Improve, deploy, and maintain models prepared by Data Scientists into production-grade cloud systems using scalable, efficient machine learning operations pipelines.
• Write and refine code to ensure performance and reliability of data extraction and processing.
• Lead requirements gathering sessions with business and technical staff to distill technical requirements from business requests.
• Develop advanced SQL queries to extract data for analysis and model construction.
• Own delivery of large, complex data and ML engineering projects.
• Design and develop scalable, efficient data pipeline processes to handle data ingestion, cleansing, transformation, integration, and validation required to provide access to prepared data sets to analysts and data scientists.
• Ensure performance and reliability of data processes.
• Document and test data processes including performance through data validation and verification.
• Collaborate with cross-functional teams to resolve data quality and operational issues and ensure timely delivery of products.
• Develop and implement scripts for database and data process maintenance, monitoring, and performance tuning.
• Analyze and evaluate databases in order to identify and recommend improvements and optimization.
• Design advanced eye-catching visualizations to convey information to users.

Requirements

• Bachelor's degree and 5 years of experience with Data Warehouses and Data Lakes, Big Data platforms and programming in Python, R or other related language.
• Understanding of ML Algorithms, experience creating & executing efficient MLOps pipelines, and tuning ML models.
• Familiarity with large language models and with implementation of AI solutions in a cloud environment.
• In lieu of degree, 7 years of the experience as stated above.