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I’m Pavan Kumar Gummuluru, an AI/ML engineer with 4 years of experience designing, developing, and deploying data-driven solutions across healthcare, e-commerce, finance, and manufacturing. I specialize in machine learning, deep learning (CNN, RNN, Transformers), NLP (LLMs, BERT, GPT), and computer vision (YOLO, OpenCV), with strong MLOps capabilities using MLflow, TensorFlow Serving, TorchServe, Docker, Kubernetes, and CI/CD to enable scalable, production-grade deployments on AWS SageMaker, GCP Vertex AI, and Azure ML. I’ve built predictive, CV, and NLP solutions that drive measurable business impact and ensure regulatory compliance. I excel at bridging business needs with AI-driven innovation through clear stakeholder communication and robust documentation. I pursue collaborative, end-to-end solutions—from data engineering with Spark and Airflow to model development and deployment—delivering tangible improvements in accuracy, efficiency, and compliance while partnering with clinical and business teams to frame problems and translate insights into action.…I’m Pavan Kumar Gummuluru, an AI/ML engineer with 4 years of experience designing, developing, and deploying data-driven solutions across healthcare, e-commerce, finance, and manufacturing. I specialize in machine learning, deep learning (CNN, RNN, Transformers), NLP (LLMs, BERT, GPT), and computer vision (YOLO, OpenCV), with strong MLOps capabilities using MLflow, TensorFlow Serving, TorchServe, Docker, Kubernetes, and CI/CD to enable scalable, production-grade deployments on AWS SageMaker, GCP Vertex AI, and Azure ML. I’ve built predictive, CV, and NLP solutions that drive measurable business impact and ensure regulatory compliance. I excel at bridging business needs with AI-driven innovation through clear stakeholder communication and robust documentation. I pursue collaborative, end-to-end solutions—from data engineering with Spark and Airflow to model development and deployment—delivering tangible improvements in accuracy, efficiency, and compliance while partnering with clinical and business teams to frame problems and translate insights into action.

PAVAN KUMAR GUMMULURU

Data Scientist, AI Engineer, Full Stack Developer, +4

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I’m Pavan Kumar Gummuluru, an AI/ML engineer with 4 years of experience designing, developing, and deploying data-driven solutions across healthcare, e-commerce, finance, and manufacturing. I specialize in machine learning, deep learning (CNN, RNN, Transformers), NLP (LLMs, BERT, GPT), and computer vision (YOLO, OpenCV), with strong MLOps capabilities using MLflow, TensorFlow Serving, TorchServe, Docker, Kubernetes, and CI/CD to enable scalable, production-grade deployments on AWS SageMaker, GCP Vertex AI, and Azure ML. I’ve built predictive, CV, and NLP solutions that drive measurable business impact and ensure regulatory compliance. I excel at bridging business needs with AI-driven innovation through clear stakeholder communication and robust documentation. I pursue collaborative, end-to-end solutions—from data engineering with Spark and Airflow to model development and deployment—delivering tangible improvements in accuracy, efficiency, and compliance while partnering with clinical and business teams to frame problems and translate insights into action.…I’m Pavan Kumar Gummuluru, an AI/ML engineer with 4 years of experience designing, developing, and deploying data-driven solutions across healthcare, e-commerce, finance, and manufacturing. I specialize in machine learning, deep learning (CNN, RNN, Transformers), NLP (LLMs, BERT, GPT), and computer vision (YOLO, OpenCV), with strong MLOps capabilities using MLflow, TensorFlow Serving, TorchServe, Docker, Kubernetes, and CI/CD to enable scalable, production-grade deployments on AWS SageMaker, GCP Vertex AI, and Azure ML. I’ve built predictive, CV, and NLP solutions that drive measurable business impact and ensure regulatory compliance. I excel at bridging business needs with AI-driven innovation through clear stakeholder communication and robust documentation. I pursue collaborative, end-to-end solutions—from data engineering with Spark and Airflow to model development and deployment—delivering tangible improvements in accuracy, efficiency, and compliance while partnering with clinical and business teams to frame problems and translate insights into action.

Available to hire

I’m Pavan Kumar Gummuluru, an AI/ML engineer with 4 years of experience designing, developing, and deploying data-driven solutions across healthcare, e-commerce, finance, and manufacturing. I specialize in machine learning, deep learning (CNN, RNN, Transformers), NLP (LLMs, BERT, GPT), and computer vision (YOLO, OpenCV), with strong MLOps capabilities using MLflow, TensorFlow Serving, TorchServe, Docker, Kubernetes, and CI/CD to enable scalable, production-grade deployments on AWS SageMaker, GCP Vertex AI, and Azure ML. I’ve built predictive, CV, and NLP solutions that drive measurable business impact and ensure regulatory compliance.

I excel at bridging business needs with AI-driven innovation through clear stakeholder communication and robust documentation. I pursue collaborative, end-to-end solutions—from data engineering with Spark and Airflow to model development and deployment—delivering tangible improvements in accuracy, efficiency, and compliance while partnering with clinical and business teams to frame problems and translate insights into action.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Work Experience

AI Engineer at Cardinal Health

December 1, 2024 - Present

Designed and deployed predictive models to forecast patient readmissions and medication adherence using XGBoost, random forest, and LSTM networks, improving prediction accuracy by 18%. Developed computer vision pipelines with YOLO and OpenCV for medical inventory tracking and anomaly detection in radiology scans, reducing manual review time by 25%. Implemented NLP-driven clinical note analysis leveraging BERT/GPT models and RAG systems to extract key medical entities and automate documentation, saving 12+ hours/week for physicians. Deployed scalable AI models with MLflow, Docker, and Kubernetes integrated into AWS SageMaker for real-time healthcare workflows, ensuring HIPAA compliance.

ML Engineer at Orion Technolab

July 1, 2023 - October 24, 2025

Developed recommendation systems for e-commerce clients using collaborative filtering, matrix factorization, and deep learning, boosting click-through rates by 22%. Implemented fraud detection models for financial clients using ensemble methods (XGBoost, LightGBM), reducing false positives by 15%. Built customer sentiment analysis pipelines with Hugging Face transformers to analyze social media and support tickets, enabling proactive client engagement. Created image classification and defect detection models with CNNs and OpenCV for manufacturing clients, reducing quality control errors by 30%. Automated ETL workflows with Apache Spark and Airflow, improving data pipeline efficiency and reducing processing time by 40%. Deployed ML solutions using GCP Vertex AI and Azure ML, ensuring scalability across client infrastructures.

AI Engineer at Cardinal Health

December 1, 2024 - November 26, 2025

ML Engineer at Orion Technolab

July 1, 2023 - July 1, 2023