Available to hire
Hi there! I’m Varun Sai Gattamaneni, a strategic and impact-driven AI/ML Engineer based in New Jersey. I design, build, and deploy production-grade ML systems, optimize data pipelines, and collaborate with data scientists to translate complex business needs into scalable, data-driven solutions that drive measurable results.
I have hands-on experience across healthcare, enterprise IT, and cloud-native environments, with a track record of reducing data processing latency and delivering end-to-end ML pipelines. I thrive on solving hard problems with Python, cloud platforms, and modern MLOps practices.
Language
English
Fluent
Work Experience
AI/ML Data Engineer at CoreWeave
September 30, 2025 - October 23, 2025Designed, built, and optimized data pipelines to support large-scale AI/ML training and inference workloads on GPU clusters. Developed and deployed ETL workflows using Python, SQL, and Apache Airflow, ensuring efficient data ingestion, transformation, and validation. Collaborated with data scientists to prepare high-quality training datasets and automate feature extraction processes. Deployed machine learning models to production environments using Docker, Kubernetes, and CoreWeave GPU infrastructure. Implemented data versioning, model tracking, and experiment management with MLflow and DVC. Integrated and managed cloud storage and compute resources (AWS S3, GCP Storage, CoreWeave Cloud) for scalable ML workloads. Monitored and optimized pipeline performance, reducing data processing latency by 30–40% through caching and parallelization. Built real-time data streaming solutions using Kafka and Spark Streaming to support online model serving and analytics. Conducted data quality check
AI/ML Data Engineer at Elevance Health
September 30, 2024 - October 23, 2025Architected and automated scalable end-to-end data pipelines to enable high-performance ML model training, validation, and deployment across multiple healthcare domains. Engineered and optimized data ingestion, cleansing, and transformation workflows using Python, PySpark, and SQL, processing large-scale structured and unstructured datasets with speed, accuracy, and scalability. Collaborated with data scientists and ML engineers to design centralized feature stores, ensuring consistent, versioned, and reusable datasets for production ML systems. Developed and modernized ETL/ELT pipelines leveraging AWS (S3, Glue, Lambda, Redshift) and Azure Data Factory, improving data throughput by 40% and reducing model training latency. Implemented MLOps and DataOps best practices, automating model retraining, deployment, experiment tracking, and performance monitoring with MLflow, Airflow, Docker, Kubernetes, and GitHub Actions.
AI/ML Engineer at Zensar Technologies
July 31, 2022 - October 23, 2025Engineered and deployed supervised and unsupervised ML models for classification, regression, clustering, and anomaly detection, delivering actionable insights that improved business decision-making. Designed and implemented scalable end-to-end ML pipelines using Python, TensorFlow, PyTorch, and Scikit-learn, ensuring seamless integration from data ingestion to production deployment. Developed advanced NLP applications including sentiment analysis, named entity recognition, and document summarization leveraging spaCy, BERT, and Transformers. Built and optimized computer vision models for image classification, object detection, and image segmentation using OpenCV, YOLOv5, and PyTorch. Integrated ML solutions into production via FastAPI, Flask, Docker, and Kubernetes, achieving high reliability, low-latency inference, and scalable deployments. Automated ML workflows for training, testing, and deployment using Apache Airflow and MLflow, significantly reducing manual effort and improving r
AI/ML Engineering Internship at FABIN TECHNOLOGIES
January 1, 2021 - October 23, 2025As an AI/ML Intern, I built and deployed machine learning models to solve key business problems. Using XGBoost, I enhanced churn prediction through advanced feature engineering and tuning. I also developed sentiment analysis with spaCy and BERT, deploying scalable APIs via Flask and Docker with strong MLOps practices.
Education
Masters Computer Science at Rowan University
January 11, 2030 - January 1, 2024Qualifications
Industry Experience
Computers & Electronics, Healthcare, Education, Software & Internet, Professional Services
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