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AI/ML Engineer with 3+ years of experience designing, building, and deploying scalable machine learning systems and intelligent applications across high-growth tech, HR-tech, and enterprise environments. Hands-on expertise with Python, Apache Spark, PyTorch, TensorFlow, FastAPI, AWS, and Kubernetes, with a strong foundation in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), MLOps, Apache Kafka, MLflow, and Databricks. Proven track record delivering production-ready AI solutions that process millions of daily transactions, reduce operational costs, and accelerate decision-making for cross-functional teams. Experienced in end-to-end ML life-cycle management from feature engineering and model training to CI/CD pipelines, experiment tracking, and real-time model monitoring at scale.…AI/ML Engineer with 3+ years of experience designing, building, and deploying scalable machine learning systems and intelligent applications across high-growth tech, HR-tech, and enterprise environments. Hands-on expertise with Python, Apache Spark, PyTorch, TensorFlow, FastAPI, AWS, and Kubernetes, with a strong foundation in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), MLOps, Apache Kafka, MLflow, and Databricks. Proven track record delivering production-ready AI solutions that process millions of daily transactions, reduce operational costs, and accelerate decision-making for cross-functional teams. Experienced in end-to-end ML life-cycle management from feature engineering and model training to CI/CD pipelines, experiment tracking, and real-time model monitoring at scale.

Param Madan

AI Engineer, AI Developer, AI Strategy Consultant, +2

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AI/ML Engineer with 3+ years of experience designing, building, and deploying scalable machine learning systems and intelligent applications across high-growth tech, HR-tech, and enterprise environments. Hands-on expertise with Python, Apache Spark, PyTorch, TensorFlow, FastAPI, AWS, and Kubernetes, with a strong foundation in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), MLOps, Apache Kafka, MLflow, and Databricks. Proven track record delivering production-ready AI solutions that process millions of daily transactions, reduce operational costs, and accelerate decision-making for cross-functional teams. Experienced in end-to-end ML life-cycle management from feature engineering and model training to CI/CD pipelines, experiment tracking, and real-time model monitoring at scale.…AI/ML Engineer with 3+ years of experience designing, building, and deploying scalable machine learning systems and intelligent applications across high-growth tech, HR-tech, and enterprise environments. Hands-on expertise with Python, Apache Spark, PyTorch, TensorFlow, FastAPI, AWS, and Kubernetes, with a strong foundation in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), MLOps, Apache Kafka, MLflow, and Databricks. Proven track record delivering production-ready AI solutions that process millions of daily transactions, reduce operational costs, and accelerate decision-making for cross-functional teams. Experienced in end-to-end ML life-cycle management from feature engineering and model training to CI/CD pipelines, experiment tracking, and real-time model monitoring at scale.

Available to hire

AI/ML Engineer with 3+ years of experience designing, building, and deploying scalable machine learning systems and intelligent applications across high-growth tech, HR-tech, and enterprise environments. Hands-on expertise with Python, Apache Spark, PyTorch, TensorFlow, FastAPI, AWS, and Kubernetes, with a strong foundation in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), MLOps, Apache Kafka, MLflow, and Databricks.

Proven track record delivering production-ready AI solutions that process millions of daily transactions, reduce operational costs, and accelerate decision-making for cross-functional teams. Experienced in end-to-end ML life-cycle management from feature engineering and model training to CI/CD pipelines, experiment tracking, and real-time model monitoring at scale.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Advanced

Work Experience

AI/ML Engineer at Uber

January 1, 2026 - Present

Architected real-time demand forecasting pipelines across 100+ metropolitan zones using Python and Spark to support accurate driver supply planning during peak demand. Engineered pricing models using Apache Kafka, XGBoost, and feature stores, deploying 12+ production models for fare estimates and surge recommendations on high-volume transactions. Optimized online inference services using PyTorch, Docker, and Kubernetes to process 800K+ prediction requests daily with sub-second latency for rider and driver applications. Orchestrated ML workflows using Airflow, MLflow, and Amazon SageMaker across multiple stakeholders to streamline model validation and production release cycles. Championed generative AI initiatives using LangChain, vector databases, and LLM frameworks to deliver support assistants and knowledge retrieval workflows.

AI/ML Consultant at Massachusetts Institute of Technology - Spinout (AutonomUS)

July 1, 2024 - December 1, 2024

Architected a battlefield surgical robotics system to automate wound detection across 14 trauma scenarios using real-time ultrasound imaging and CNNs. Optimized deep learning U-Net models in PyTorch and CUDA to eliminate probabilistic risk conditions through rigorous peer-reviewed code changes. Orchestrated production pipelines tracking model drift across 25,000 validation ultrasound frames, translating technical risks into concrete milestones for executive stakeholders. Overhauled end-to-end architecture planning and deployment to meet a 0.8-second processing latency target by unifying engineering workflows. Supported deployment to satisfy military medical standards by building compliance verification frameworks based on technical rigor and cross-team alignment.

Software Developer at Dell Technologies

June 1, 2021 - July 1, 2023

Developed backend modules using Python, FastAPI, and PostgreSQL managing 25K+ enterprise devices across 8 operational workflows for internal asset management. Engineered data processing components with Pandas and SQL to collect, clean, and transform 500K+ device events for reporting dashboards and predictive analytics. Integrated prediction services with Scikit-learn and XGBoost into backend APIs for hardware health assessments across 5 infrastructure monitoring systems. Automated build and deployment using Docker and Jenkins for 15+ Python services across development, testing, and production environments. Implemented ML integration workflows by validating and deploying 6+ predictive models into enterprise support platforms, coordinating API contracts with data science teams.