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I'm Divya Reddy, an AI/ML Engineer with a passion for turning data into actionable insights and scalable production solutions. I have four years of hands-on experience designing, training, deploying, and monitoring machine learning and deep learning models across healthcare and enterprise platforms. I excel across the full ML lifecycle—from data ingestion and feature engineering to model development, evaluation, and retraining—delivering predictive analytics that drive business impact. I’m proficient with Python-based ML frameworks like scikit-learn, TensorFlow, PyTorch, and XGBoost, and I routinely build scalable pipelines with Airflow, MLflow, and Docker. I also design and deploy ML inference services via FastAPI and REST architectures, work with both structured and unstructured data, and apply NLP techniques for text preprocessing and sentiment analysis. My experience spans cloud environments (AWS, GCP, Azure) for ML workloads, cross-functional collaboration in Agile teams, and HIPAA-compliant data handling for healthcare projects. I enjoy turning insights into production-ready solutions and collaborating with data engineers, product managers, and stakeholders to drive business outcomes.…I'm Divya Reddy, an AI/ML Engineer with a passion for turning data into actionable insights and scalable production solutions. I have four years of hands-on experience designing, training, deploying, and monitoring machine learning and deep learning models across healthcare and enterprise platforms. I excel across the full ML lifecycle—from data ingestion and feature engineering to model development, evaluation, and retraining—delivering predictive analytics that drive business impact. I’m proficient with Python-based ML frameworks like scikit-learn, TensorFlow, PyTorch, and XGBoost, and I routinely build scalable pipelines with Airflow, MLflow, and Docker. I also design and deploy ML inference services via FastAPI and REST architectures, work with both structured and unstructured data, and apply NLP techniques for text preprocessing and sentiment analysis. My experience spans cloud environments (AWS, GCP, Azure) for ML workloads, cross-functional collaboration in Agile teams, and HIPAA-compliant data handling for healthcare projects. I enjoy turning insights into production-ready solutions and collaborating with data engineers, product managers, and stakeholders to drive business outcomes.

Divya Reddy

AI Engineer, Data Scientist, Programmer, +3

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I'm Divya Reddy, an AI/ML Engineer with a passion for turning data into actionable insights and scalable production solutions. I have four years of hands-on experience designing, training, deploying, and monitoring machine learning and deep learning models across healthcare and enterprise platforms. I excel across the full ML lifecycle—from data ingestion and feature engineering to model development, evaluation, and retraining—delivering predictive analytics that drive business impact. I’m proficient with Python-based ML frameworks like scikit-learn, TensorFlow, PyTorch, and XGBoost, and I routinely build scalable pipelines with Airflow, MLflow, and Docker. I also design and deploy ML inference services via FastAPI and REST architectures, work with both structured and unstructured data, and apply NLP techniques for text preprocessing and sentiment analysis. My experience spans cloud environments (AWS, GCP, Azure) for ML workloads, cross-functional collaboration in Agile teams, and HIPAA-compliant data handling for healthcare projects. I enjoy turning insights into production-ready solutions and collaborating with data engineers, product managers, and stakeholders to drive business outcomes.…I'm Divya Reddy, an AI/ML Engineer with a passion for turning data into actionable insights and scalable production solutions. I have four years of hands-on experience designing, training, deploying, and monitoring machine learning and deep learning models across healthcare and enterprise platforms. I excel across the full ML lifecycle—from data ingestion and feature engineering to model development, evaluation, and retraining—delivering predictive analytics that drive business impact. I’m proficient with Python-based ML frameworks like scikit-learn, TensorFlow, PyTorch, and XGBoost, and I routinely build scalable pipelines with Airflow, MLflow, and Docker. I also design and deploy ML inference services via FastAPI and REST architectures, work with both structured and unstructured data, and apply NLP techniques for text preprocessing and sentiment analysis. My experience spans cloud environments (AWS, GCP, Azure) for ML workloads, cross-functional collaboration in Agile teams, and HIPAA-compliant data handling for healthcare projects. I enjoy turning insights into production-ready solutions and collaborating with data engineers, product managers, and stakeholders to drive business outcomes.

Available to hire

I’m Divya Reddy, an AI/ML Engineer with a passion for turning data into actionable insights and scalable production solutions. I have four years of hands-on experience designing, training, deploying, and monitoring machine learning and deep learning models across healthcare and enterprise platforms. I excel across the full ML lifecycle—from data ingestion and feature engineering to model development, evaluation, and retraining—delivering predictive analytics that drive business impact. I’m proficient with Python-based ML frameworks like scikit-learn, TensorFlow, PyTorch, and XGBoost, and I routinely build scalable pipelines with Airflow, MLflow, and Docker.

I also design and deploy ML inference services via FastAPI and REST architectures, work with both structured and unstructured data, and apply NLP techniques for text preprocessing and sentiment analysis. My experience spans cloud environments (AWS, GCP, Azure) for ML workloads, cross-functional collaboration in Agile teams, and HIPAA-compliant data handling for healthcare projects. I enjoy turning insights into production-ready solutions and collaborating with data engineers, product managers, and stakeholders to drive business outcomes.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

English

Fluent

Work Experience

AI / ML Engineer at Humana

January 1, 2025 - Present

Designed and trained machine learning models for healthcare risk prediction and patient outcome analysis using Python and scikit-learn. Built end-to-end ML pipelines including data preprocessing, feature engineering, model training, and validation using Pandas, NumPy, and Airflow. Developed NLP models to analyze unstructured clinical notes and claims data with SpaCy and transformer-based embeddings. Improved model accuracy by 25% through advanced feature engineering and hyperparameter optimization. Implemented model explainability using SHAP and feature importance techniques to improve clinical trust and regulatory transparency. Deployed trained models as scalable REST APIs using FastAPI and Docker on AWS and GCP environments. Built batch inference workflows for large scale prediction jobs using Airflow and cloud storage. Implemented model tracking, versioning, and performance monitoring using MLflow. Monitored model drift and data distribution changes and triggered automated retrainin

Machine Learning Engineer at Cisco

September 1, 2023 - December 1, 2025

Developed predictive analytics models for customer behavior analysis and enterprise decision support systems. Performed extensive exploratory data analysis and feature engineering to improve model robustness and performance. Built deep learning models using TensorFlow and PyTorch for anomaly detection and pattern recognition use cases. Developed time series forecasting models to predict demand trends and seasonal patterns. Deployed ML models as microservices using Flask and Docker for internal enterprise applications. Optimized model inference latency by improving preprocessing logic and deployment configurations. Integrated ML outputs into BI dashboards for business stakeholders and leadership teams. Applied cross validation and hyperparameter tuning techniques to improve generalization. Participated in Agile sprint planning, reviews, and retrospectives using Jira.

Junior AI Engineer at Enterprise Analytics Platform

July 1, 2021 - December 1, 2022

Assisted in building and validating machine learning models for sales forecasting and operational analytics to support business planning and decision making initiatives. Prepared, cleaned, and transformed large structured datasets using Python and SQL, ensuring data quality, consistency, and readiness for machine learning model consumption. Implemented clustering and dimensionality reduction techniques such as K Means and PCA to support exploratory data analysis and identify hidden patterns in business data. Built basic NLP pipelines for text preprocessing, tokenization, and sentiment analysis on customer feedback and internal text datasets. Created detailed model performance reports and interactive visualizations using Matplotlib and Power BI to communicate insights to analysts and stakeholders. Supported senior ML engineers in model testing, deployment, and post deployment monitoring activities to ensure stable and reliable model performance. Gained hands on exposure to cloud based M