Looks like you have JavaScript disabled. For the full Twine experience, you will need to re-enable it.

I am a results-oriented machine learning engineer with 6+ years of experience designing, deploying, and optimizing AI/ML systems across enterprise and cloud environments. I specialize in building Generative AI applications, MLOps frameworks, and end-to-end ML pipelines using Databricks, MLflow, LangChain, Azure ML, and AWS SageMaker. I have a proven track record of improving model accuracy, automating workflows, and delivering scalable, production-ready solutions that drive measurable business impact.…I am a results-oriented machine learning engineer with 6+ years of experience designing, deploying, and optimizing AI/ML systems across enterprise and cloud environments. I specialize in building Generative AI applications, MLOps frameworks, and end-to-end ML pipelines using Databricks, MLflow, LangChain, Azure ML, and AWS SageMaker. I have a proven track record of improving model accuracy, automating workflows, and delivering scalable, production-ready solutions that drive measurable business impact.

Sai Keerthi

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





I am a results-oriented machine learning engineer with 6+ years of experience designing, deploying, and optimizing AI/ML systems across enterprise and cloud environments. I specialize in building Generative AI applications, MLOps frameworks, and end-to-end ML pipelines using Databricks, MLflow, LangChain, Azure ML, and AWS SageMaker. I have a proven track record of improving model accuracy, automating workflows, and delivering scalable, production-ready solutions that drive measurable business impact.…I am a results-oriented machine learning engineer with 6+ years of experience designing, deploying, and optimizing AI/ML systems across enterprise and cloud environments. I specialize in building Generative AI applications, MLOps frameworks, and end-to-end ML pipelines using Databricks, MLflow, LangChain, Azure ML, and AWS SageMaker. I have a proven track record of improving model accuracy, automating workflows, and delivering scalable, production-ready solutions that drive measurable business impact.

Available to hire

I am a results-oriented machine learning engineer with 6+ years of experience designing, deploying, and optimizing AI/ML systems across enterprise and cloud environments.

I specialize in building Generative AI applications, MLOps frameworks, and end-to-end ML pipelines using Databricks, MLflow, LangChain, Azure ML, and AWS SageMaker. I have a proven track record of improving model accuracy, automating workflows, and delivering scalable, production-ready solutions that drive measurable business impact.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Work Experience

Machine Learning Engineer at Nirvana Health, RxAdvance Corporation, MA

February 1, 2023 - Present

Designed and deployed scalable ML pipelines using Databricks and MLflow, reducing training time by 35%. Built a Generative AI chatbot using LangChain and OpenAI API for internal documentation retrieval (RAG-based), cutting response time by 60%. Developed predictive deep learning models for patient analytics, improving diagnostic accuracy by 18%. Containerized and deployed ML models using Docker and Kubernetes via Azure ML endpoints. Automated large-scale data preprocessing using Airflow and PySpark for multi-terabyte data pipelines. Collaborated with DevOps and engineering teams to create real-time model monitoring dashboards using Prometheus and Grafana.

Machine Learning Engineer at Kendriya Vidyalaya, India

June 1, 2019 - November 1, 2021

Designed and implemented machine learning models to analyze student performance and predict attendance trends, enhancing intervention accuracy by 25%. Engineered and maintained data preprocessing and feature extraction pipelines using Python, Pandas, and NumPy for improved model accuracy. Conducted exploratory data analysis (EDA) and visualized academic insights through Power BI and Matplotlib dashboards. Automated SQL-based reporting workflows, reducing manual data processing time by 30%. Collaborated with IT teams to migrate data pipelines to Azure Cloud, enabling scalable storage and real-time access to educational datasets. Deployed ML models and integrated predictive insights into decision-making dashboards for academic administrators.