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I am Sai Babu Karre, an AI/ML Engineer with 5+ years of experience designing, deploying, and maintaining scalable cloud-native AI/ML solutions on AWS. I specialize in Python, machine learning, and MLOps, with hands-on experience building and operationalizing AI/ML workflows using LLaMA, LangChain, Generative AI, CNNs, deep learning, LLMs, and NLP, while leveraging PostgreSQL, XGBoost, and TensorFlow for efficient model training and deployment. I’m skilled at data visualization and analytics with Tableau and Power BI, translating complex model outputs into actionable insights for business and technical stakeholders. I build end-to-end ML pipelines with reliability and reproducibility, integrating with AWS for enterprise-grade solutions, and I enjoy collaborating across teams to deliver impactful AI solutions from data exploration to production.…I am Sai Babu Karre, an AI/ML Engineer with 5+ years of experience designing, deploying, and maintaining scalable cloud-native AI/ML solutions on AWS. I specialize in Python, machine learning, and MLOps, with hands-on experience building and operationalizing AI/ML workflows using LLaMA, LangChain, Generative AI, CNNs, deep learning, LLMs, and NLP, while leveraging PostgreSQL, XGBoost, and TensorFlow for efficient model training and deployment. I’m skilled at data visualization and analytics with Tableau and Power BI, translating complex model outputs into actionable insights for business and technical stakeholders. I build end-to-end ML pipelines with reliability and reproducibility, integrating with AWS for enterprise-grade solutions, and I enjoy collaborating across teams to deliver impactful AI solutions from data exploration to production.

Sai Babu Karre

AI Engineer, Data Scientist, Programmer, +3

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I am Sai Babu Karre, an AI/ML Engineer with 5+ years of experience designing, deploying, and maintaining scalable cloud-native AI/ML solutions on AWS. I specialize in Python, machine learning, and MLOps, with hands-on experience building and operationalizing AI/ML workflows using LLaMA, LangChain, Generative AI, CNNs, deep learning, LLMs, and NLP, while leveraging PostgreSQL, XGBoost, and TensorFlow for efficient model training and deployment. I’m skilled at data visualization and analytics with Tableau and Power BI, translating complex model outputs into actionable insights for business and technical stakeholders. I build end-to-end ML pipelines with reliability and reproducibility, integrating with AWS for enterprise-grade solutions, and I enjoy collaborating across teams to deliver impactful AI solutions from data exploration to production.…I am Sai Babu Karre, an AI/ML Engineer with 5+ years of experience designing, deploying, and maintaining scalable cloud-native AI/ML solutions on AWS. I specialize in Python, machine learning, and MLOps, with hands-on experience building and operationalizing AI/ML workflows using LLaMA, LangChain, Generative AI, CNNs, deep learning, LLMs, and NLP, while leveraging PostgreSQL, XGBoost, and TensorFlow for efficient model training and deployment. I’m skilled at data visualization and analytics with Tableau and Power BI, translating complex model outputs into actionable insights for business and technical stakeholders. I build end-to-end ML pipelines with reliability and reproducibility, integrating with AWS for enterprise-grade solutions, and I enjoy collaborating across teams to deliver impactful AI solutions from data exploration to production.

Available to hire

I am Sai Babu Karre, an AI/ML Engineer with 5+ years of experience designing, deploying, and maintaining scalable cloud-native AI/ML solutions on AWS. I specialize in Python, machine learning, and MLOps, with hands-on experience building and operationalizing AI/ML workflows using LLaMA, LangChain, Generative AI, CNNs, deep learning, LLMs, and NLP, while leveraging PostgreSQL, XGBoost, and TensorFlow for efficient model training and deployment.

I’m skilled at data visualization and analytics with Tableau and Power BI, translating complex model outputs into actionable insights for business and technical stakeholders. I build end-to-end ML pipelines with reliability and reproducibility, integrating with AWS for enterprise-grade solutions, and I enjoy collaborating across teams to deliver impactful AI solutions from data exploration to production.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

AI/ML Engineer at S&P Global

January 1, 2025 - Present

Built regression pipelines leveraging Python, Scikit-learn, and TensorFlow, resulting in a 35% reduction in model training time while maintaining high prediction precision. Implemented NLP techniques, including sentiment analysis, named entity recognition, and XGBoost-based classification models, increasing text classification accuracy by 32% for real-time applications. Automated CI/CD pipelines for ML models integrated with AWS S3 for efficient data storage and model artifact management, streamlining version control, scalability, and faster time-to-market for AI solutions. Developed end-to-end AI/ML architectures using LangChain orchestration, large language models, and hybrid retrieval-augmented generation (RAG) pipelines, achieving a 40% faster inference speed with scalable deployment. Designed scalable training pipelines for LLaMA, GPT-4, BERT, and other GenAI models using PyTorch and Hugging Face, improving data processing throughput by 35% while ensuring reproducibility and effic

AI/ML Engineer at Groovy Webs

September 1, 2020 - August 1, 2023

Executed Decision Tree-based classification and regression pipelines, boosting model explainability for stakeholders, and achieving a 25% faster decision-support system deployment. Implemented knowledge graphs and vector-based indexing using LlamaIndex and machine learning models with Scikit-learn to enhance enterprise search, leading to a 40% improvement in user satisfaction scores. Optimized large-scale ETL pipelines in AWS Redshift, delivering a 25% improvement in query performance and reducing overall processing costs through schema design, while integrating NLP techniques to enhance text processing and analytics. Deployed machine learning and deep learning models leveraging Python, TensorFlow, and Convolutional Neural Networks (CNNs), improving predictive accuracy by 35% and reducing model training workflows and scalable pipelines. Enhanced Power BI dashboards leveraging advanced DAX functions, enabling AI/ML teams to visualize complex model outputs, resulting in a 30% improvement

AI/ML Engineer at HCL

January 1, 2019 - August 1, 2020

Improved Random Forest models for classification and regression tasks, improving prediction accuracy by 18% and reducing model overfitting through hyperparameter tuning and feature engineering. Conducted performance evaluation and hyperparameter tuning of Deep Learning models, improving model robustness and achieving a 30% increase in prediction efficiency across multiple datasets. Employed real-time data pipelines using AWS Kinesis, improving streaming data processing efficiency by 35%, and Tableau dashboards to visualize insights, enabling faster machine learning models across production environments. Established data visualizations using Matplotlib to represent complex AI/ML model results, improving insight clarity by 35% and enabling faster stakeholder decision-making across projects. Performed and maintained ETL processes using SQL Server, reducing data processing time and supporting machine learning workflows that increased operational efficiency and automated analytics reporting