Mohd Sarique

Kalyani, IN.

About

Work

DeepSolv
|

AI Intern

Summary

Developed a complex Graph RAG architecture for social media comment moderation, resulting in significant improvements in accuracy and reducing manual review time by 40%, enhancing overall operational efficiency.

Highlights

Tech-Stack: Langgraph,, Python, FAST-API, Docker, Prometheus, MySQL, Kubernetes

Skills: GenAI, RAG, NLP, Backend Development, GCP, BigQuery

Zeron
|

DataScience -SDE Intern

Summary

Engineered a Retrieval-Augmented Generation (RAG) system for cybersecurity compliance reviews, achieving 95% accuracy after fine-tuning the LlamaIndex-7b LLM model, thus improving review efficiency by 60%.

Highlights

Tech-Stack: Langchain, LlamIndex-7b, Python, Transformers, Ragas

Skills: Machine Learning, NLP, Analytics, Google Cloud

Pollux
|

AI Engineering Intern

Summary

Contributed to the content generation pipeline by integrating various diffusion models and engineered an SDK for AI services which served as the backbone of AI services. Set up the backend pipeline for image storage and retrieval from cloud storage, reducing time by 40%.

Highlights

Tech-Stack: Tensorflow, Pytorch, Numpy, SQL, VertexAI

Skills: Machine Learning, Programming, Data Analysis, GenerativeAI

Indian Institute of Science Education and Research
|

Research Intern

Summary

Machine Learning and NLP: Developed a NER-based dataset extractor from research papers. Integrated the GROBID server services in the code for file conversion.

Highlights

Tech-Stack:Python, GROBID, NLP

Education

Indian Institute Of Information technology Kalyani

Bachelor of Technology

Computer Science and Engineering

Grade: 8.66/10

Awards

3 star rated coder on codechef and leetcode

Awarded By

Codechef Profile☑ Leetcode Profile

NTSE (National Talent Search Examination)

Qualified stage I, was among top 1 percentile candidates at state level.

NMTC (National Mathematics Talent Contest)

Qualified stage I, was among the top 1 percentile candidates at the national level.

Skills

Languages

C, C++, Python.

Tech Stack

Pytorch, Docker, BigQuery, VertexAI, Langgraph, Langchain, FAST API, Google Cloud.

Projects

Doc Chat

Summary

A LLM chatbot built using Dollyv2, langchain that allows you to chat with your document data conveniently, It works on RAG and embeddings for retrieval.

Whos My Doc

Summary

A full-stack doctor booking site for both patients and doctors, with specified slots, ML-based clustering used for doctor selection.

Vid2Pdf

Summary

Engineered a Python application, Vid2Pdf, leveraging image processing and subtitle extraction to convert videos into PDF documents, achieving a 95% accuracy rate in text conversion for videos under 10 minutes