Suraj Chatterjee

About Suraj Chatterjee

I am a Machine Learning Engineer with a passion for solving complex problems. Throughout my career, I have worked on a wide range of projects and have gained extensive experience in developing machine learning models and algorithms that deliver real-world value. But beyond my technical skills, what sets me apart is my unwavering commitment to finding innovative solutions to the toughest challenges.As a problem solver at heart, I thrive in dynamic environments where I can apply my skills to make a difference. I am driven by a desire to create positive change through technology and to make a lasting impact on the world around me. Whether I am working on a new project or collaborating with others to tackle a complex problem, I bring a relentless focus and unwavering dedication to every task at hand.If you are looking for a passionate and skilled Machine Learning Engineer with a proven track record of success, I would love to connect with you.

Experience

1. Machine Learning Engineer

   Collinson Group

   May 2024 — Present

   Working on a chatbot based on LLM with RAG implementation using vector databases using AWS services like Bedrock, Lambda, S3 buckets, etc and LLM models such as Llama2, Claude, etc. Designed and implemented Generative AI solutions, including LLM-based intelligent chatbots using RAG (Retrieval-Augmented Generation) architecture with Langchain, LangGraph, AWS Bedrock, Llama2, Claude, GPT,vector databases (FAISS, Qdrant, ChromaDB, Pinecone) and explored finetuning LLMs (LoRA, QLoRA). Developed scalable ML pipelines for traditional ML, NLP and GenAI models using Amazon SageMaker, Bedrock, EC2, Lambda, ECS, ECR, S3, Terraform and Snowflake adhering to MLOps best practices for versioning, CI/CD, and model monitoring. Integrated serverless backend APIs for AI services using AWS Lambda and deployed them using API Gateway and Terraform. Contributed to real-time AI monitoring dashboards and performance reporting using Python-based visualization libraries, Streamlit and Amazon CloudWatch logs. Explored and implemented NLP, AI & LLM techniques in NLP tasks like entity resolution, question answering, text summarization, and semantic search, with a focus on scalability, latency, and response accuracy. Embraced MLOps workflows, using Github Actions, Docker and Terraform for containerization and infrastructure provisioning, and monitored deployments through CloudWatch.

Education

• SARDAR VALLABHBHAI PATEL Junior College of Science and Commerce

  HSC

  2015 — 2017

• St. Francis Institute Of Technology

  Bachelor's degree, Information Technology

  2017 — 2021

• St. Francis Xavier High School

  SSC

  2005 — 2015