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• AI/ML Engineer with 9+ years of extensive experience in designing, developing, and deploying scalable Machine Learning, Deep Learning, and Artificial Intelligence solutions that drive business intelligence, automation, and predictive analytics. • Strong expertise in Python, TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, Pandas, NumPy, and OpenCV for building high-performance AI applications. • Hands-on experience with Natural Language Processing (NLP), Computer Vision, Time Series Forecasting, Recommendation Systems, Anomaly Detection, and Predictive Analytics across enterprise environments. • Strong knowledge of MLOps practices using MLflow, Kubeflow, Docker, Kubernetes, Git, CI/CD pipelines, and automated model versioning, deployment, and monitoring.…• AI/ML Engineer with 9+ years of extensive experience in designing, developing, and deploying scalable Machine Learning, Deep Learning, and Artificial Intelligence solutions that drive business intelligence, automation, and predictive analytics. • Strong expertise in Python, TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, Pandas, NumPy, and OpenCV for building high-performance AI applications. • Hands-on experience with Natural Language Processing (NLP), Computer Vision, Time Series Forecasting, Recommendation Systems, Anomaly Detection, and Predictive Analytics across enterprise environments. • Strong knowledge of MLOps practices using MLflow, Kubeflow, Docker, Kubernetes, Git, CI/CD pipelines, and automated model versioning, deployment, and monitoring.

Sai Kumar Reddy

AI Engineer, Data Scientist, AI Developer, +2

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• AI/ML Engineer with 9+ years of extensive experience in designing, developing, and deploying scalable Machine Learning, Deep Learning, and Artificial Intelligence solutions that drive business intelligence, automation, and predictive analytics. • Strong expertise in Python, TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, Pandas, NumPy, and OpenCV for building high-performance AI applications. • Hands-on experience with Natural Language Processing (NLP), Computer Vision, Time Series Forecasting, Recommendation Systems, Anomaly Detection, and Predictive Analytics across enterprise environments. • Strong knowledge of MLOps practices using MLflow, Kubeflow, Docker, Kubernetes, Git, CI/CD pipelines, and automated model versioning, deployment, and monitoring.…• AI/ML Engineer with 9+ years of extensive experience in designing, developing, and deploying scalable Machine Learning, Deep Learning, and Artificial Intelligence solutions that drive business intelligence, automation, and predictive analytics. • Strong expertise in Python, TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, Pandas, NumPy, and OpenCV for building high-performance AI applications. • Hands-on experience with Natural Language Processing (NLP), Computer Vision, Time Series Forecasting, Recommendation Systems, Anomaly Detection, and Predictive Analytics across enterprise environments. • Strong knowledge of MLOps practices using MLflow, Kubeflow, Docker, Kubernetes, Git, CI/CD pipelines, and automated model versioning, deployment, and monitoring.

Available to hire

• AI/ML Engineer with 9+ years of extensive experience in designing, developing, and deploying scalable Machine Learning, Deep Learning, and Artificial Intelligence solutions that drive business intelligence, automation, and predictive analytics.
• Strong expertise in Python, TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, Pandas, NumPy, and OpenCV for building high-performance AI applications.
• Hands-on experience with Natural Language Processing (NLP), Computer Vision, Time Series Forecasting, Recommendation Systems, Anomaly Detection, and Predictive Analytics across enterprise environments.
• Strong knowledge of MLOps practices using MLflow, Kubeflow, Docker, Kubernetes, Git, CI/CD pipelines, and automated model versioning, deployment, and monitoring.

Skills

Work Experience

AI/ML Engineer at PNC Bank

May 1, 2025 - Present

Designed, developed, and deployed scalable machine learning and deep learning models to solve business problems and improve operational efficiency. Built end-to-end AI/ML pipelines for ingestion, preprocessing, feature engineering, training, tuning, evaluation, deployment, and continuous monitoring. Developed NLP solutions (classification, sentiment, NER, summarization, intelligent search) and Generative AI systems using LLMs, prompt engineering, and RAG with vector databases (FAISS/Pinecone/ChromaDB). Implemented REST APIs with FastAPI and Flask and applied MLOps practices with MLflow, Docker, Kubernetes, Git, and CI/CD for versioning, deployment, and monitoring. Optimized model performance via feature engineering/selection, cross-validation, and hyperparameter tuning, and ensured production reliability using monitoring, drift detection, and automated retraining.

AI/ML Engineer at Macy’s

January 1, 2023 - April 30, 2025

Built scalable AI/ML solutions to automate business processes and improve operational efficiency across enterprise applications. Developed predictive analytics and classification models; created reusable feature engineering frameworks to improve accuracy and reduce training time. Implemented recommendation/personalization models based on customer behavior. Built scalable data preprocessing and validation workflows to improve training data quality. Applied hyperparameter tuning, cross-validation, ensemble methods, and performance benchmarking. Worked on distributed processing using Python, PySpark, and Spark, and contributed to production model monitoring and stability.

ML Engineer at CVS Health

September 1, 2020 - December 31, 2022

Designed and deployed scalable ML models for enterprise predictive decision-making. Delivered end-to-end pipelines (data collection, preprocessing, feature engineering, training, evaluation, deployment, monitoring). Built classification, regression, clustering, recommendation, and forecasting solutions. Implemented FastAPI/Flask REST APIs and applied MLOps using MLflow, Docker, Kubernetes, Git, and CI/CD. Created automated data validation, retraining, and monitoring workflows; applied deep learning for image recognition, text analytics, and predictive modeling while integrating models via secure microservices and APIs.

ML Engineer / Data Science at Thermo Fisher Scientific

July 1, 2018 - August 31, 2020

Developed and deployed scalable machine learning and data science solutions to produce actionable insights. Built ML pipelines covering acquisition, preprocessing, feature engineering, training, validation, deployment, and monitoring. Developed supervised/unsupervised/ensemble models for classification, regression, clustering, forecasting, and anomaly detection. Implemented NLP and Generative AI (LLMs, prompt engineering, RAG, LangChain, vector databases). Applied MLOps (MLflow, Docker, Kubernetes, CI/CD), improved explainability (feature importance, SHAP), and created dashboards using Power BI/Tableau/Matplotlib. Automated data processing and analytical workflows and supported long-term reliability via monitoring and drift detection.

Data Science at Sonata Software

November 1, 2016 - March 31, 2018

Designed and built data science solutions to analyze datasets and support strategic decision-making. Performed data collection, cleaning, transformation, and validation for large structured/unstructured data. Conducted EDA and statistical analysis to identify trends and correlations. Built predictive models for classification, regression, clustering, forecasting, and anomaly detection. Developed NLP solutions and deep learning models for image and text analytics. Created dashboards and reporting, and implemented reusable pipelines for automated preparation, feature extraction, model training, and reporting. Supported hypothesis testing and A/B testing.