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I'm an AI/ML engineer with ~3 years of hands-on experience across machine learning systems, data engineering pipelines, and GenAI applications in mobility and pharmaceutical analytics. I have built real-time inference and streaming solutions using Python, TensorFlow, Kafka, Spark, and cloud platforms, turning complex data into actionable insights. Beyond modeling, I design robust ML ops, GenAI workflows with LangChain and OpenAI integrations, and scalable deployments on AWS, Databricks, Snowflake, Kubernetes, and Airflow. I enjoy collaborating with cross-functional teams to ship practical AI-powered features that improve user experiences and business outcomes.…I'm an AI/ML engineer with ~3 years of hands-on experience across machine learning systems, data engineering pipelines, and GenAI applications in mobility and pharmaceutical analytics. I have built real-time inference and streaming solutions using Python, TensorFlow, Kafka, Spark, and cloud platforms, turning complex data into actionable insights. Beyond modeling, I design robust ML ops, GenAI workflows with LangChain and OpenAI integrations, and scalable deployments on AWS, Databricks, Snowflake, Kubernetes, and Airflow. I enjoy collaborating with cross-functional teams to ship practical AI-powered features that improve user experiences and business outcomes.

Madan Kumar Banda

AI Engineer, Data Scientist, Full Stack Developer, +2

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I'm an AI/ML engineer with ~3 years of hands-on experience across machine learning systems, data engineering pipelines, and GenAI applications in mobility and pharmaceutical analytics. I have built real-time inference and streaming solutions using Python, TensorFlow, Kafka, Spark, and cloud platforms, turning complex data into actionable insights. Beyond modeling, I design robust ML ops, GenAI workflows with LangChain and OpenAI integrations, and scalable deployments on AWS, Databricks, Snowflake, Kubernetes, and Airflow. I enjoy collaborating with cross-functional teams to ship practical AI-powered features that improve user experiences and business outcomes.…I'm an AI/ML engineer with ~3 years of hands-on experience across machine learning systems, data engineering pipelines, and GenAI applications in mobility and pharmaceutical analytics. I have built real-time inference and streaming solutions using Python, TensorFlow, Kafka, Spark, and cloud platforms, turning complex data into actionable insights. Beyond modeling, I design robust ML ops, GenAI workflows with LangChain and OpenAI integrations, and scalable deployments on AWS, Databricks, Snowflake, Kubernetes, and Airflow. I enjoy collaborating with cross-functional teams to ship practical AI-powered features that improve user experiences and business outcomes.

Available to hire

I’m an AI/ML engineer with ~3 years of hands-on experience across machine learning systems, data engineering pipelines, and GenAI applications in mobility and pharmaceutical analytics. I have built real-time inference and streaming solutions using Python, TensorFlow, Kafka, Spark, and cloud platforms, turning complex data into actionable insights.

Beyond modeling, I design robust ML ops, GenAI workflows with LangChain and OpenAI integrations, and scalable deployments on AWS, Databricks, Snowflake, Kubernetes, and Airflow. I enjoy collaborating with cross-functional teams to ship practical AI-powered features that improve user experiences and business outcomes.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Work Experience

AI/ML Engineer at Uber

March 1, 2026 - Present

Optimized TensorFlow-based dispatch pipelines processing 120K+ daily rider events via Apache Kafka, reducing inference latency from 320ms to 180ms and increasing dispatch responsiveness. Contributed to RAG-based GenAI support systems using OpenAI APIs, LangChain, and retrieval workflows, improving automated support resolution accuracy by ~20% across 12K+ weekly rider and driver interactions. Integrated LLM-powered conversational automation within Kubernetes-based environments, supporting 12K+ weekly customer interactions with 140ms response latency and reducing manual support escalations by 18%. Supported refinement of PySpark feature engineering workflows on Databricks for large-scale transportation telemetry, enabling downstream fraud detection, anomaly monitoring, and risk modeling.

Machine Learning Teaching Assistant at The George Washington University

September 1, 2025 - December 1, 2025

Reviewed and debugged 50+ student implementations weekly across Neural Networks, CNNs, and model evaluation assignments; ensured code quality, reproducibility, and adherence to machine learning best practices. Guided students during office hours and assignment reviews on Python, TensorFlow, and model debugging techniques, helping improve implementation accuracy across supervised learning and deep learning coursework.

Data Analytics Engineer at Cipla

June 1, 2021 - December 1, 2023

Consolidated AWS Glue ingestion pipelines processing 3 million pharmaceutical manufacturing records weekly, eliminating 12 duplicate validation workflows across clinical compliance and operational reporting environments. Optimized Apache Spark ETL transformations handling 2 TB nightly, reducing batch completion windows from 8 hours to 3 hours across distributed Hadoop clusters. Automated SQL-based anomaly detection frameworks validating 120K+ patient and inventory records daily, preventing downstream reporting discrepancies within enterprise regulatory submission pipelines. Engineered Tableau dashboards integrating Amazon Redshift warehousing layers, enabling leadership teams to analyze 95 manufacturing KPIs spanning procurement, logistics, compliance, and supply-chain forecasting operations. Migrated dbt transformation models into Apache Airflow orchestration environments supporting 48 enterprise analytics datasets, decreasing manual reconciliation workloads by 22 operational hours mo