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Hi, I'm Sai Kiran Tupakula, an AI/ML Engineer with over 5 years of experience designing, developing, and deploying scalable ML and AI solutions for enterprise environments. I specialize in transforming raw data into actionable insights, building end-to-end ML pipelines, and delivering production-grade models that drive business value. I’m proficient in Python, Scikit-learn, TensorFlow, XGBoost, and MLOps/CI/CD pipelines, and I have hands-on experience with Generative AI, BERT, and GPT-4 for advanced NLP applications such as Named Entity Recognition. I work across AWS, Azure, and GCP and create dashboards in Tableau and Power BI to visualize results and inform strategic decisions.…Hi, I'm Sai Kiran Tupakula, an AI/ML Engineer with over 5 years of experience designing, developing, and deploying scalable ML and AI solutions for enterprise environments. I specialize in transforming raw data into actionable insights, building end-to-end ML pipelines, and delivering production-grade models that drive business value. I’m proficient in Python, Scikit-learn, TensorFlow, XGBoost, and MLOps/CI/CD pipelines, and I have hands-on experience with Generative AI, BERT, and GPT-4 for advanced NLP applications such as Named Entity Recognition. I work across AWS, Azure, and GCP and create dashboards in Tableau and Power BI to visualize results and inform strategic decisions.

Sai Kiran Tupakula

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

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Hi, I'm Sai Kiran Tupakula, an AI/ML Engineer with over 5 years of experience designing, developing, and deploying scalable ML and AI solutions for enterprise environments. I specialize in transforming raw data into actionable insights, building end-to-end ML pipelines, and delivering production-grade models that drive business value. I’m proficient in Python, Scikit-learn, TensorFlow, XGBoost, and MLOps/CI/CD pipelines, and I have hands-on experience with Generative AI, BERT, and GPT-4 for advanced NLP applications such as Named Entity Recognition. I work across AWS, Azure, and GCP and create dashboards in Tableau and Power BI to visualize results and inform strategic decisions.…Hi, I'm Sai Kiran Tupakula, an AI/ML Engineer with over 5 years of experience designing, developing, and deploying scalable ML and AI solutions for enterprise environments. I specialize in transforming raw data into actionable insights, building end-to-end ML pipelines, and delivering production-grade models that drive business value. I’m proficient in Python, Scikit-learn, TensorFlow, XGBoost, and MLOps/CI/CD pipelines, and I have hands-on experience with Generative AI, BERT, and GPT-4 for advanced NLP applications such as Named Entity Recognition. I work across AWS, Azure, and GCP and create dashboards in Tableau and Power BI to visualize results and inform strategic decisions.

Available to hire

Hi, I’m Sai Kiran Tupakula, an AI/ML Engineer with over 5 years of experience designing, developing, and deploying scalable ML and AI solutions for enterprise environments. I specialize in transforming raw data into actionable insights, building end-to-end ML pipelines, and delivering production-grade models that drive business value.

I’m proficient in Python, Scikit-learn, TensorFlow, XGBoost, and MLOps/CI/CD pipelines, and I have hands-on experience with Generative AI, BERT, and GPT-4 for advanced NLP applications such as Named Entity Recognition. I work across AWS, Azure, and GCP and create dashboards in Tableau and Power BI to visualize results and inform strategic decisions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Work Experience

AI/ML Engineer at State Street

January 1, 2025 - November 19, 2025

Established multiple ML pipelines leveraging Regression Models with feature engineering, hyperparameter tuning, and cross-validation. Implemented an automated MLflow + CI/CD pipeline, reducing manual intervention and expediting deployment of production-ready ML models by 65%. Built domain-specific LLaMA models for NLU tasks, achieving substantial gains in semantic accuracy and reduced hallucinations through adaptive tokenization and prompt-tuning across multilingual data. Created AWS-based ML infrastructure (EMR, EC2) integrated with Scikit-learn and XGBoost, and visualized outcomes via Tableau dashboards for faster model-to-insight delivery. Developed GAN-based data augmentation workflows with LangChain to enhance synthetic data quality for context-aware conversational AI. Deployed hybrid LLM architectures combining BERT for contextual embeddings and GPT-4 for generative reasoning, boosting natural language inference accuracy and chatbot fluency. Applied TensorFlow-based deep learning

AI/ML Engineer at KPIT

November 30, 2022 - November 30, 2022

Implemented Decision Tree and Random Forest models for customer churn prediction, with hyperparameter tuning to improve performance. Conducted Hypothesis Testing and CNN-based image recognition tasks, achieving notable improvements in classification accuracy. Enhanced Retrieval-Augmented Generation (RAG) pipelines by integrating LLMs with contextual vector databases for more relevant enterprise chatbot responses. Developed NER systems using spaCy and custom-trained transformers to automate entity extraction. Improved scalable data pipelines using Azure Data Lake and Data Storage, automating ingestion and processing of high-volume data and increasing processing efficiency. Performed EDA with Python libraries (NumPy, Pandas, Matplotlib) to derive actionable insights that improved forecasting accuracy by 30%. Designed scalable relational databases with PostgreSQL to prepare model-ready datasets.