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AI/ML Engineer with 3+ years of experience designing and deploying scalable machine learning and deep learning solutions. Skilled in developing end-to-end ML pipelines, predictive modeling, NLP, and computer vision applications using Python, TensorFlow, and PyTorch. Experienced in MLOps, cloud deployment (AWS SageMaker, Docker, Airflow), and model monitoring for production-grade systems. Proficient in transforming complex data into actionable insights through advanced analytics and visualization tools such as Power BI and Streamlit. Recognized for improving predictive accuracy, optimizing workflows, and delivering data-driven innovation while maintaining compliance and data integrity standards…AI/ML Engineer with 3+ years of experience designing and deploying scalable machine learning and deep learning solutions. Skilled in developing end-to-end ML pipelines, predictive modeling, NLP, and computer vision applications using Python, TensorFlow, and PyTorch. Experienced in MLOps, cloud deployment (AWS SageMaker, Docker, Airflow), and model monitoring for production-grade systems. Proficient in transforming complex data into actionable insights through advanced analytics and visualization tools such as Power BI and Streamlit. Recognized for improving predictive accuracy, optimizing workflows, and delivering data-driven innovation while maintaining compliance and data integrity standards

Venkatesh Seenu

Data Scientist, AI Engineer, Full Stack Developer, +2

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AI/ML Engineer with 3+ years of experience designing and deploying scalable machine learning and deep learning solutions. Skilled in developing end-to-end ML pipelines, predictive modeling, NLP, and computer vision applications using Python, TensorFlow, and PyTorch. Experienced in MLOps, cloud deployment (AWS SageMaker, Docker, Airflow), and model monitoring for production-grade systems. Proficient in transforming complex data into actionable insights through advanced analytics and visualization tools such as Power BI and Streamlit. Recognized for improving predictive accuracy, optimizing workflows, and delivering data-driven innovation while maintaining compliance and data integrity standards…AI/ML Engineer with 3+ years of experience designing and deploying scalable machine learning and deep learning solutions. Skilled in developing end-to-end ML pipelines, predictive modeling, NLP, and computer vision applications using Python, TensorFlow, and PyTorch. Experienced in MLOps, cloud deployment (AWS SageMaker, Docker, Airflow), and model monitoring for production-grade systems. Proficient in transforming complex data into actionable insights through advanced analytics and visualization tools such as Power BI and Streamlit. Recognized for improving predictive accuracy, optimizing workflows, and delivering data-driven innovation while maintaining compliance and data integrity standards

Available to hire

AI/ML Engineer with 3+ years of experience designing and deploying scalable machine learning and deep learning solutions. Skilled
in developing end-to-end ML pipelines, predictive modeling, NLP, and computer vision applications using Python, TensorFlow, and
PyTorch. Experienced in MLOps, cloud deployment (AWS SageMaker, Docker, Airflow), and model monitoring for production-grade
systems. Proficient in transforming complex data into actionable insights through advanced analytics and visualization tools such
as Power BI and Streamlit. Recognized for improving predictive accuracy, optimizing workflows, and delivering data-driven
innovation while maintaining compliance and data integrity standards

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Advanced

Work Experience

AI/ML Engineer at Humana

February 1, 2025 - November 18, 2025

Designed and implemented end-to-end ML pipelines to predict patient readmission and disease risk scores using Python, TensorFlow, and scikit-learn; improved model recall for high-risk patients by 18%. Performed data preprocessing and feature extraction on large-scale healthcare datasets with HIPAA-compliant handling of PHI data using PySpark and AWS Glue for distributed processing. Developed and tuned ensemble models (XGBoost, Random Forest, Logistic Regression) for risk stratification and integrated into clinical decision support systems. Deployed ML models into production using AWS SageMaker and Dockerized microservices, enabling real-time risk scoring via API. Built interactive Power BI dashboards and Streamlit apps to visualize patient risk segments and population health trends, driving preventive care initiatives.

Machine Learning Engineer at Cyient

June 1, 2023 - June 1, 2023

Designed and implemented end-to-end ML pipelines for driver behaviour classification and predictive maintenance using Python, scikit-learn, and TensorFlow. Performed feature engineering on large-scale telematics datasets (CAN bus, GPS, accelerometer) to extract indicators of driver habits, braking patterns, and fuel efficiency. Developed time-series forecasting models and anomaly detection algorithms using XGBoost and LSTM networks, improving component failure prediction accuracy by 27%. Built data ingestion and preprocessing workflows using PySpark and AWS S3, reducing ETL time by 40% through efficient data partitioning and caching. Collaborated with data scientists and automotive engineers to validate ML outputs against real-world vehicle test data. Deployed trained models as microservices via Docker and FastAPI, integrating with OEM’s cloud-based telematics dashboard for real-time insights. Created interactive dashboards in Power BI and Streamlit to visualize driver performance me