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Poojhaa Chandrasekaran

@poojhaachandrasekara

AI/ML Engineer at AltaML improving LLM response accuracy by 38% with RAG workflows.

At AltaML, I build Python and SQL pipelines on AWS and Snowflake for financial records and predictive modeling. I also develop classification models and LLM and RAG workflows, improving response accuracy by 38%.

I deploy FastAPI inference services in Docker and automate ML releases with Apache Airflow and CI/CD pipelines. That work cut response delays by 33% and reduced release effort by 40%.

At Flipkart, I built recommendation models and demand forecasting models for inventory planning. I also developed ETL pipelines that improved data availability by 35%.

Experience

Work history, roles, and key accomplishments

Current

AI/ML Engineer

Current

AltaML

Apr 2026 - Present (7 months)

Build and maintain Python and SQL pipelines on AWS and Snowflake, preparing 1M+ financial records for predictive modeling and investment analytics. Develop classification and predictive models in scikit-learn and PyTorch, and engineer LLM and RAG workflows improving response accuracy by 38%.

Python SQL AWS Snowflake scikit learn PyTorch LLM RAG Prompt Engineering Embeddings Vector Search fastAPI Docker Airflow CI CD Model Monitoring Drift Detection

AI/ML Engineer Intern

AltaML

Sep 2025 - Mar 2026 (6 months)

Streamlined Python and SQL workflows for structured financial datasets, reducing data preparation time by 41%. Trained and evaluated classification and regression models in scikit-learn, and prototyped LLM and RAG capabilities.

Python SQL scikit learn LLM RAG Embeddings Vector Search Prompt Tuning Data Validation Experimentation

Junior AI/ML Engineer

Flipkart

Jan 2022 - Aug 2024 (2 years 7 months)

Built recommendation models in Python, Pandas, and scikit-learn to support personalized product recommendations and upselling. Developed demand forecasting models and established ETL pipelines processing 5M+ records weekly.