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I am a driven AI/ML Engineer with 3 years of experience designing end-to-end machine learning solutions for predictive analytics and intelligent automation. I build and deploy models using Python, Scikit-learn, and AWS SageMaker, with expertise in NLP, time-series forecasting, and data-driven optimization. I collaborate with cross-functional teams to integrate ML workflows into scalable systems using Docker, Airflow, SQL, and Power BI. I am committed to delivering high-impact insights through continuous model tuning, monitoring, and stakeholder-aligned results.…I am a driven AI/ML Engineer with 3 years of experience designing end-to-end machine learning solutions for predictive analytics and intelligent automation. I build and deploy models using Python, Scikit-learn, and AWS SageMaker, with expertise in NLP, time-series forecasting, and data-driven optimization. I collaborate with cross-functional teams to integrate ML workflows into scalable systems using Docker, Airflow, SQL, and Power BI. I am committed to delivering high-impact insights through continuous model tuning, monitoring, and stakeholder-aligned results.

Sai Prasanth Kaligotla

AI Engineer, Data Scientist, Developer, +5

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I am a driven AI/ML Engineer with 3 years of experience designing end-to-end machine learning solutions for predictive analytics and intelligent automation. I build and deploy models using Python, Scikit-learn, and AWS SageMaker, with expertise in NLP, time-series forecasting, and data-driven optimization. I collaborate with cross-functional teams to integrate ML workflows into scalable systems using Docker, Airflow, SQL, and Power BI. I am committed to delivering high-impact insights through continuous model tuning, monitoring, and stakeholder-aligned results.…I am a driven AI/ML Engineer with 3 years of experience designing end-to-end machine learning solutions for predictive analytics and intelligent automation. I build and deploy models using Python, Scikit-learn, and AWS SageMaker, with expertise in NLP, time-series forecasting, and data-driven optimization. I collaborate with cross-functional teams to integrate ML workflows into scalable systems using Docker, Airflow, SQL, and Power BI. I am committed to delivering high-impact insights through continuous model tuning, monitoring, and stakeholder-aligned results.

Available to hire

I am a driven AI/ML Engineer with 3 years of experience designing end-to-end machine learning solutions for predictive analytics and intelligent automation. I build and deploy models using Python, Scikit-learn, and AWS SageMaker, with expertise in NLP, time-series forecasting, and data-driven optimization.

I collaborate with cross-functional teams to integrate ML workflows into scalable systems using Docker, Airflow, SQL, and Power BI. I am committed to delivering high-impact insights through continuous model tuning, monitoring, and stakeholder-aligned results.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Advanced

Work Experience

AI/ML Engineer at Fifth Third Bank

February 1, 2025 - Present

Engineered end-to-end machine learning workflows for early risk identification by analyzing customer behavioral and credit data using Python, SQL, and Jupyter. Built interpretable classification models with decision trees and boosting algorithms to enhance risk scoring, integrating insights into Power BI dashboards. Automated model training and deployment with AWS SageMaker and Git, supporting real-time loan processing. Used Apache Airflow for pipeline automation and scheduling daily batch processing and retraining. Collaborated with business stakeholders using SHAP-based explanations to improve model transparency. Addressed data quality issues with robust imputation and proxy variable strategies. Monitored data imbalance and model drift with real-time tools, applying corrective sampling and calibration to maintain model performance.

Machine Learning Engineer at Hellinex Cloud

July 1, 2023 - August 20, 2025

Designed and implemented ML pipelines in Python and SQL to analyze cloud infrastructure logs and support ticket metadata for time-series forecasting and issue classification. Developed regression and classification models using Scikit-learn, XGBoost, LightGBM, CatBoost, Logistic Regression, and Prophet to improve IT resource forecasting and incident resolution automation. Created NLP workflows using SpaCy, NLTK, Gensim, and advanced text preprocessing to classify support requests by urgency, intent, and sentiment. Deployed models through FastAPI, Docker, Kubernetes, and integrated with AWS SageMaker and ServiceNow. Automated training, retraining, and data validation with Apache Airflow and monitored performance with AWS CloudWatch, Prometheus, and Grafana. Delivered dynamic dashboards in Power BI and Tableau for stakeholders, collaborated using Git and Jenkins, and triggered real-time predictions with AWS Lambda.

AI/ML Engineer at Fifth Third Bank, USA

February 1, 2025 - Present

Engineered end-to-end ML workflows for SmartRisk Insight that analyzed customer behavioral and credit data to enable early risk identification. Built interpretable classification models using decision trees and boosting to enhance risk scoring and integrated insights into Power BI dashboards. Automated loan scoring pipelines with Apache Airflow for daily batch processing including retraining. Collaborated with underwriters and risk officers to improve feature selection and used SHAP for model explanation. Applied robust statistical imputation methods to handle missing data and monitored model drift using real-time tools to maintain accuracy and scalability in production deployment.

Machine Learning Engineer at Hellinex Cloud, India

July 1, 2023 - August 26, 2025

Designed and implemented ML pipelines analyzing cloud infrastructure logs and support ticket metadata for time-series forecasting and issue classification. Developed regression and classification models using Scikit-learn, XGBoost, LightGBM, CatBoost, and Prophet to improve IT resource forecasting and automated incident resolution. Engineered NLP workflows with SpaCy, NLTK, and Gensim for support request classification by urgency and sentiment. Deployed models using FastAPI, Docker, Kubernetes, and AWS SageMaker integrated with tools like ServiceNow. Automated training, retraining, and validation processes with Apache Airflow and monitored model performance using AWS CloudWatch, Prometheus, and Grafana. Created dashboards in Power BI and Tableau to deliver operational KPIs. Managed version control using Git and Jenkins while enabling real-time predictions via AWS Lambda.

AI/ML Engineer at Fifth Third Bank, USA

February 1, 2025 - Present

Led end-to-end ML workflows for SmartRisk Insight, extracting and analyzing customer behavioral and credit data (Python, SQL, Jupyter) to enable early risk identification. Built interpretable classification models and integrated insights into Power BI dashboards for risk analytics. Streamlined training and deployment using AWS SageMaker and Git, enabling secure real-time loan-processing endpoints. Automated loan application scoring pipelines with Apache Airflow for daily batch processing and retraining. Collaborated with underwriters to incorporate SHAP explanations into predictive dashboards and addressed data quality issues with robust imputation and feature derivation. Monitored data balance and drift with real-time monitoring, applying sampling and calibration to preserve performance.

Machine Learning Engineer at Hellinex Cloud, India

July 1, 2023 - October 15, 2025

Designed and implemented robust ML pipelines using Python, SQL, Pandas, and NumPy to analyze cloud infrastructure logs and support ticket metadata for time-series forecasting and issue categorization. Developed regression and classification models using Scikit-learn, XGBoost, LightGBM, CatBoost, Logistic Regression, and Prophet, significantly improving IT resource forecasting and automated incident resolution. Engineered NLP workflows (SpaCy, NLTK, Gensim, TF-IDF, Bag-of-Words) to classify support requests by urgency, intent, and sentiment. Deployed models with FastAPI, Docker, Kubernetes, and integrated with AWS SageMaker; enabled CI/CD via Jenkins and GitHub Actions. Automated training, retraining, and data validation using Apache Airflow; monitored via CloudWatch, Prometheus, Grafana. Created dashboards in Power BI, Tableau, and Excel; triggered real-time predictions via AWS Lambda. Applied Ridge/Lasso, Decision Trees, Random Forest, SVM, and KNN to ensure accurate results.