Summary
Serjesh Sharma is a Machine Learning Platform Engineering Manager with over a decade of hands-on experience building and scaling MLOps platforms across cloud and on-prem environments. He has led teams at Workday, Ford, and McKinsey to productionize ML for high-stakes domains—advancing ADAS pipelines on GCP, architecting secure ML platforms on AWS, and standardizing feature stores and experimentation workflows. Comfortable spanning data engineering, model deployment, and infrastructure, he has practical expertise with BigQuery, DataFlow, Airflow, Databricks, MLflow and Kubernetes-driven strategies. Known for turning legacy systems into reliable, auditable pipelines, he has repeatedly improved reliability and delivery cadence while aligning ML engineering with business objectives. Based in Atlanta, he combines an MS in Analytics from Georgia Tech with a background in large-scale ETL and real-time systems, bringing pragmatic systems thinking to complex AI initiatives.
10 years of coding experience
16 years of employment as a software developer
B. Tech COMPUTER SCIENCE AND ENGINEERING, B. Tech COMPUTER SCIENCE AND ENGINEERING at Indian Institute of Technology (Indian School of Mines), Dhanbad
Master of Science - MS Analytics, Master of Science - MS Analytics at Georgia Institute of Technology