I am an AI/ML Engineer with 5+ years of experience delivering scalable enterprise AI and machine learning solutions across consulting and technology environments. I design and deploy end-to-end ML pipelines using PyTorch, Scikit-learn, and Apache Spark, improving model performance on fraud detection, churn, and demand forecasting with datasets of 20M+ records.
I accelerate deployment by building robust MLOps with MLflow, Docker, and CI/CD, enabling real-time inference that handles thousands of predictions per minute. I build streaming and batch architectures with Kafka and Spark Streaming to generate near real-time insights from millions of daily events, and I translate complex business challenges into production-grade AI solutions deployed across AWS and Azure, delivering measurable impact in risk analytics, customer intelligence, and forecasting.
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