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Hi, I’m Sanjita Chandan Ballapur, a Columbia Engineering MS candidate specializing in Machine Learning, currently based in New York. I love building end-to-end AI solutions and exploring NLP, computer vision, and responsible AI. I’m passionate about turning data into insights and scalable systems. I have hands-on experience from HPE and startups, including real-time gesture and speech interfaces, data pipeline optimization, and NLP model fine-tuning, with projects spanning ML for ancient language translation and stock prediction.…Hi, I’m Sanjita Chandan Ballapur, a Columbia Engineering MS candidate specializing in Machine Learning, currently based in New York. I love building end-to-end AI solutions and exploring NLP, computer vision, and responsible AI. I’m passionate about turning data into insights and scalable systems. I have hands-on experience from HPE and startups, including real-time gesture and speech interfaces, data pipeline optimization, and NLP model fine-tuning, with projects spanning ML for ancient language translation and stock prediction.

Sanjita Chandan Ballapur

AI Engineer, AI Developer, Cloud Developer, +1

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Hi, I’m Sanjita Chandan Ballapur, a Columbia Engineering MS candidate specializing in Machine Learning, currently based in New York. I love building end-to-end AI solutions and exploring NLP, computer vision, and responsible AI. I’m passionate about turning data into insights and scalable systems. I have hands-on experience from HPE and startups, including real-time gesture and speech interfaces, data pipeline optimization, and NLP model fine-tuning, with projects spanning ML for ancient language translation and stock prediction.…Hi, I’m Sanjita Chandan Ballapur, a Columbia Engineering MS candidate specializing in Machine Learning, currently based in New York. I love building end-to-end AI solutions and exploring NLP, computer vision, and responsible AI. I’m passionate about turning data into insights and scalable systems. I have hands-on experience from HPE and startups, including real-time gesture and speech interfaces, data pipeline optimization, and NLP model fine-tuning, with projects spanning ML for ancient language translation and stock prediction.

Available to hire

Hi, I’m Sanjita Chandan Ballapur, a Columbia Engineering MS candidate specializing in Machine Learning, currently based in New York. I love building end-to-end AI solutions and exploring NLP, computer vision, and responsible AI. I’m passionate about turning data into insights and scalable systems.

I have hands-on experience from HPE and startups, including real-time gesture and speech interfaces, data pipeline optimization, and NLP model fine-tuning, with projects spanning ML for ancient language translation and stock prediction.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Data Engineer at Hewlett Packard Enterprise (HPE), Bangalore

September 1, 2024 - June 1, 2025

Led the end-to-end migration of software applications from cloud to on-premises clusters with security requirements. Re-architected data pipelines to enable multi-environment deployment. Designed a structured storage strategy for compacted Kafka topics using Delta Lake, reducing latency and storage costs by 50%.

College Intern at Hewlett Packard Enterprise (HPE), Bangalore

February 1, 2024 - August 1, 2024

Optimized data pipelines with Spark and Kafka to handle large-scale, multi-format data efficiently. Integrated protobuf support into Spark/Kafka pipelines, enabling faster serialization/deserialization and reducing compute costs by eliminating Avro conversion overhead.

Machine Learning Intern at Troogue.ai, Bangalore

June 1, 2023 - September 1, 2023

Developed an ML/NLP system to analyze resumes and generate insights, improving candidate-job matching accuracy. Created datasets and trained models (BERT, Word2Vec, Logistic Regression, Random Forest, Decision Tree) to extract and rank technical experience and skills. Deployed models as scalable API endpoints via microservices in collaboration with cross-functional teams.