Hire Lakshminarayana J. - MLOps Engineer

Designed and implemented Enterprise MLOps Platform includes major capabilities such as: model development tooling for developing AI models, testing/validation models, continuous integration, sdk for deploying models, feature store pipelines with supporting repository and API for feature serving capabilities, runtime AI orchestration execution, data and monitoring & Responsible AI explain-ability capabilities to ensure components meet Responsible AI. Leveraged Docker, Kubernetes, Kubeflow, MLflow, Kserve, CI/CD tools, JupyterLab, Feast, AWS Developed Python libraries for in-house MLOps platform’s Python SDK. Used for rapid development and deployment of machine learning applications to production Working with product teams across anthem to on-board ML application to in-house low-code ML platform

Leveraged advanced AI/ML techniques in Digital Claim Examiner Pipeline to automate claim processing, reducing the manual claims processing effort by 70%. Developed two models out of four different models such as detecting duplicates, likely to reject, checking benefit package & predicting authorization code. Created complex data pipelines in the cloud to support model training in lower environments and to serve the models in production. Leveraged python, PySpark, advanced SQL and AWS glue Dockerize and deployed to models for predictions as Kubernetes pods. Created monitoring pipeline to track the model performance using Kubernetes and Splunk

Designed, implemented, and maintained scalable HDFS/Hadoop or Big data platform. Created data pipelines for data ingestion from RDBMS and maintained ETL for data processing of structure and unstructured files. Worked closely with data governance and data security team to apply security policies on the platform. Experienced in high-volume data parsing/cleaning/analyzing. Developed and maintained the Data Warehouse or Analytics platform for business analysis and reporting needs. Worked on data models and data marts creation. Implemented ETL process for data integration, Data extraction, data cleansing, data transformation and to load data to Data warehouse. Carried out performance tuning on data bases and ETL