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I am a results-driven AI/ML Engineer with 5+ years of experience delivering end-to-end machine learning and deep learning solutions across healthcare and consulting domains. I specialize in building scalable AI solutions, NLP pipelines, and production-grade deployments using Python, Spark, and cloud platforms. I thrive in collaborative, Agile environments and enjoy turning data into measurable business impact. In my work, I deploy models on AWS/Azure/GCP with Docker and Kubernetes, lead cross-functional teams, and continuously explore innovations in Generative AI, RAG-based systems, and state-of-the-art ML techniques to drive value for patients, providers, and clients.…I am a results-driven AI/ML Engineer with 5+ years of experience delivering end-to-end machine learning and deep learning solutions across healthcare and consulting domains. I specialize in building scalable AI solutions, NLP pipelines, and production-grade deployments using Python, Spark, and cloud platforms. I thrive in collaborative, Agile environments and enjoy turning data into measurable business impact. In my work, I deploy models on AWS/Azure/GCP with Docker and Kubernetes, lead cross-functional teams, and continuously explore innovations in Generative AI, RAG-based systems, and state-of-the-art ML techniques to drive value for patients, providers, and clients.

Samyukta Reddy Vanga

AI Engineer, AI Developer, Data Scientist, +3

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I am a results-driven AI/ML Engineer with 5+ years of experience delivering end-to-end machine learning and deep learning solutions across healthcare and consulting domains. I specialize in building scalable AI solutions, NLP pipelines, and production-grade deployments using Python, Spark, and cloud platforms. I thrive in collaborative, Agile environments and enjoy turning data into measurable business impact. In my work, I deploy models on AWS/Azure/GCP with Docker and Kubernetes, lead cross-functional teams, and continuously explore innovations in Generative AI, RAG-based systems, and state-of-the-art ML techniques to drive value for patients, providers, and clients.…I am a results-driven AI/ML Engineer with 5+ years of experience delivering end-to-end machine learning and deep learning solutions across healthcare and consulting domains. I specialize in building scalable AI solutions, NLP pipelines, and production-grade deployments using Python, Spark, and cloud platforms. I thrive in collaborative, Agile environments and enjoy turning data into measurable business impact. In my work, I deploy models on AWS/Azure/GCP with Docker and Kubernetes, lead cross-functional teams, and continuously explore innovations in Generative AI, RAG-based systems, and state-of-the-art ML techniques to drive value for patients, providers, and clients.

Available to hire

I am a results-driven AI/ML Engineer with 5+ years of experience delivering end-to-end machine learning and deep learning solutions across healthcare and consulting domains. I specialize in building scalable AI solutions, NLP pipelines, and production-grade deployments using Python, Spark, and cloud platforms. I thrive in collaborative, Agile environments and enjoy turning data into measurable business impact.

In my work, I deploy models on AWS/Azure/GCP with Docker and Kubernetes, lead cross-functional teams, and continuously explore innovations in Generative AI, RAG-based systems, and state-of-the-art ML techniques to drive value for patients, providers, and clients.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Microsoft Certified Professional

Intermediate

GPT

Intermediate

Language

English

Fluent

Work Experience

AI/ML Engineer at Cigna

September 1, 2022 - Present

Developed and deployed AI-powered claims review models using Python, Scikit-learn, and TensorFlow that improved claims processing accuracy by 28% and reduced manual review time by 40%. Implemented NLP pipelines using SpaCy, BERT, and LangChain to automate claims adjudication in a HIPAA-compliant manner. Built scalable ETL pipelines with Apache Spark and Kafka for real-time anomaly detection and fraud prevention. Led the development of a Retrieval-Augmented Generation framework with GPT-3 and vector databases to support physician decision-making by providing context-aware patient history insights. Deployed AI/ML models using Docker, Kubernetes, and TensorFlow Serving on AWS and Azure to ensure scalability, fault tolerance, and 99.9% uptime. Collaborated with cross-functional teams in Agile/Scrum to align on sprint deliverables and regulatory requirements.

ML Engineer at Infinite Infolab

March 1, 2018 - September 4, 2025

Designed and trained predictive models for customer churn prediction which improved client retention rates by 18%. Developed anomaly detection pipelines using unsupervised ML algorithms such as Isolation Forests and Autoencoders to flag abnormal financial transactions in real-time. Implemented data preprocessing and feature engineering workflows ensuring high-quality datasets. Applied NLP models with NLTK and SpaCy to analyze large scale customer feedback, enhancing customer satisfaction. Leveraged Hadoop and Spark to process multi-terabyte datasets, significantly reducing model training time. Built interactive BI dashboards with Tableau and Power BI to visualize model outcomes and KPIs. Collaborated with business analysts and domain experts following a hybrid Waterfall and Agile methodology, delivering client-specific ML solutions within scope and time.

AI/ML Engineer at Cigna

September 1, 2022 - Present

Developed and deployed AI-powered claims review models using Python, Scikit-learn, and TensorFlow, improving claims processing accuracy by 28% and reducing manual review time by 40%. Implemented NLP pipelines with SpaCy, BERT, and LangChain to extract, summarize, and validate unstructured medical documents, enabling HIPAA-compliant automation of claims adjudication. Built scalable ETL pipelines with Apache Spark and Kafka for high-volume claims data, enabling near real-time anomaly detection and fraud prevention. Led development of a Retrieval-Augmented Generation (RAG) framework with GPT-3 and vector databases to provide context-aware patient history insights for physician decision support. Deployed models in production using Docker, Kubernetes, and TensorFlow Serving on AWS and Azure, ensuring scalability and 99.9% uptime. Collaborated with cross-functional teams in an Agile/Scrum environment, driving sprint deliverables and regulatory alignment.

ML Engineer at Infinite Infolab

March 1, 2018 - September 26, 2025

Designed and trained predictive models in R and Python (Scikit-learn, TensorFlow) for customer churn, improving client retention by 18%. Developed anomaly detection pipelines using Isolation Forests and Autoencoders to flag abnormal financial transactions in real time. Implemented data preprocessing and feature engineering with Pandas and NumPy to produce high-quality datasets for ML pipelines. Applied NLP models with NLTK and SpaCy to extract insights from large-scale customer feedback, driving product improvements. Leveraged Hadoop and Spark to process multi-terabyte datasets, reducing training time from hours to minutes. Built interactive dashboards in Tableau and Power BI to visualize model outcomes and KPIs, enabling data-driven decisions. Collaborated in Waterfall+Agile hybrid methodology to deliver client-specific ML solutions on time.

AI/ML Engineer at Cigna

September 1, 2022 - October 28, 2025

Developed and deployed AI-powered claims review models using Python, Scikit-learn, and TensorFlow, improving claims processing accuracy by 28% and reducing manual review time by 40%. Implemented NLP pipelines with SpaCy, BERT, and LangChain to extract, summarize, and validate unstructured medical documents, ensuring HIPAA-compliant automation of claims adjudication. Built scalable ETL pipelines with Apache Spark and Kafka for processing high-volume healthcare claims data, enabling near real-time anomaly detection and fraud prevention. Led development of a Retrieval-Augmented Generation (RAG) framework with GPT-3 and vector databases for physician support, providing context-aware patient history insights. Deployed AI/ML models in production using Docker, Kubernetes, and TensorFlow Serving on AWS and Azure, ensuring scalability, fault tolerance, and 99.9% uptime. Collaborated with cross-functional teams (data engineers, product owners, compliance) in an Agile/Scrum environment.

ML Engineer at Infinite Infolab

March 1, 2018 - March 1, 2018

Designed and trained predictive models in R and Python (Scikit-learn, TensorFlow) for customer churn prediction, improving client retention rates by 18%. Developed anomaly detection pipelines using unsupervised ML algorithms (Isolation Forests, Autoencoders) to flag abnormal financial transactions in real time. Implemented data preprocessing and feature engineering workflows with Pandas and NumPy, ensuring high-quality datasets for ML pipelines across multiple client projects. Applied NLP models with NLTK and SpaCy to extract insights from large-scale customer feedback, driving product improvements and enhancing customer satisfaction. Leveraged Hadoop and Spark to process multi-terabyte datasets, reducing model training time from hours to minutes. Built interactive BI dashboards in Tableau and Power BI to visualize model outcomes and business KPIs. Collaborated with business analysts and domain experts in a Waterfall + Agile hybrid methodology to deliver client ML solutions on time.