I build reliable, high-throughput MLOps and Generative AI platforms engineering robust solutions from prototype to scalable cloud deployment on AWS, Azure, and OCI. My core strength: orchestrating business-critical data & AI pipelines, automating CI/CD for production ML, and delivering resilient systems across multi-cloud environments.
Certified by Oracle, Databricks, Astronomer, and KodeKloud in Generative AI, Airflow, Kubernetes, and Data Science. I design high-performance ETL, RAG, agentic orchestration, and real-time Deep Learning (ViT-LSTM CV, XGBoost SHAP for XAI/Fraud Detection) with advanced stack: Snowflake, PySpark, Airflow (Certified), Kafka, Kubernetes/Docker.
My achievements include:
Multi-cloud ETL automation integrating Kafka/Snowflake, reducing latency from 30 to 5 mins.
Architected ViT-LSTM pipeline for real-time Computer Vision (SHAR) on Kubernetes.
Built fraud detection dashboards with XGBoost/SHAP/AUC 0.98, deployed via Flask & Power BI.
Ranked Top 9.82% on LeetCode (1700+ problems). Team Lead at Smart India Hackathon.
I'm actively seeking high-impact MLOps Engineer, Data Platform Specialist, or AI/ML Systems Engineer roles global product teams. Let’s connect to talk data ecosystems, ML engineering, and GenAI commercialization.
