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Hi, I'm Debrit Bhattacharyya, an AI Engineer with 2+ years of experience in developing end-to-end ML solutions across real-time environments, from data preparation and model training to evaluation, monitoring, and deployment in clouds. I'm skilled in Python, PyTorch, TensorFlow, scikit-learn, and other deep learning libraries. I'm passionate about teaching AI concepts and mentoring diverse teams. At the University of Technology Sydney, I guide hundreds of learners to build end-to-end data mining pipelines using modern frameworks and I work on RAG-based video grading and semantic search systems with LangChain, AWS, and MongoDB.…Hi, I'm Debrit Bhattacharyya, an AI Engineer with 2+ years of experience in developing end-to-end ML solutions across real-time environments, from data preparation and model training to evaluation, monitoring, and deployment in clouds. I'm skilled in Python, PyTorch, TensorFlow, scikit-learn, and other deep learning libraries. I'm passionate about teaching AI concepts and mentoring diverse teams. At the University of Technology Sydney, I guide hundreds of learners to build end-to-end data mining pipelines using modern frameworks and I work on RAG-based video grading and semantic search systems with LangChain, AWS, and MongoDB.

Debrit Bhattacharyya

AI Engineer, Data Scientist, AI Developer, +2

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Hi, I'm Debrit Bhattacharyya, an AI Engineer with 2+ years of experience in developing end-to-end ML solutions across real-time environments, from data preparation and model training to evaluation, monitoring, and deployment in clouds. I'm skilled in Python, PyTorch, TensorFlow, scikit-learn, and other deep learning libraries. I'm passionate about teaching AI concepts and mentoring diverse teams. At the University of Technology Sydney, I guide hundreds of learners to build end-to-end data mining pipelines using modern frameworks and I work on RAG-based video grading and semantic search systems with LangChain, AWS, and MongoDB.…Hi, I'm Debrit Bhattacharyya, an AI Engineer with 2+ years of experience in developing end-to-end ML solutions across real-time environments, from data preparation and model training to evaluation, monitoring, and deployment in clouds. I'm skilled in Python, PyTorch, TensorFlow, scikit-learn, and other deep learning libraries. I'm passionate about teaching AI concepts and mentoring diverse teams. At the University of Technology Sydney, I guide hundreds of learners to build end-to-end data mining pipelines using modern frameworks and I work on RAG-based video grading and semantic search systems with LangChain, AWS, and MongoDB.

Available to hire

Hi, I’m Debrit Bhattacharyya, an AI Engineer with 2+ years of experience in developing end-to-end ML solutions across real-time environments, from data preparation and model training to evaluation, monitoring, and deployment in clouds. I’m skilled in Python, PyTorch, TensorFlow, scikit-learn, and other deep learning libraries.

I’m passionate about teaching AI concepts and mentoring diverse teams. At the University of Technology Sydney, I guide hundreds of learners to build end-to-end data mining pipelines using modern frameworks and I work on RAG-based video grading and semantic search systems with LangChain, AWS, and MongoDB.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Work Experience

AI Engineer at CDAC (Center for Development of Advance Computing)

June 1, 2022 - May 31, 2023

Prepared datasets in S3 and ran reproducible SageMaker training jobs for computer vision models with PyTorch. Used SageMaker hyperparameter tuning and distributed training, logging metrics to CloudWatch and storing artifacts in S3 for experiment comparison. Evaluated models at scale with SageMaker Processing and Batch Transform, generating accuracy, precision and recall reports and analysis notebooks for stakeholders.

Technical Instructor – Artificial Intelligence at University of Technology Sydney

July 1, 2025 - Present

Teach core AI/ML concepts in python (TensorFlow, PyTorch, scikit-learn, Gymnasium) to mixed-background cohorts. Guided 100+ individuals and 20+ groups to build their end-to-end data mining pipeline using Hugging Face models. Developed a RAG-based video grading and semantic search system for UTS, using LangChain, AWS, MongoDB with LLM-powered chatbot interface for automated sentiment analysis video evaluation and intelligent transcript retrieval. Instrumented the RAG pipeline with LangSmith to evaluate retrieval quality, and benchmark LLM responses.

Research Intern at University of Technology Sydney

January 1, 2025 - June 30, 2025

Reviewed different State of The Art tracking algorithms – both transformer and non-transformer based. Implemented real time monitoring system for tracking crowds. Utilized multi-threading approach to boost performance by reducing latency. Applied unique “all-body part” method to track people even in occluded scenarios.