Mohd Aquib

Data Scientist

https://talent.gravityer.com/mohd-aquib

Data Scientist @extremenetworks

Extreme Networks

Key Strengths

Extensive experience with various Generative Adversarial Networks (GANs) including Pix2Pix, ESRGAN, Cycle-GAN, and SRGAN, demonstrating strong foundational knowledge in deep learning for image generation and enhancement.
Proficiency in Retrieval-Augmented Generation (RAG) systems, as evidenced by projects like 'Medical-RAG-LLM' and 'RAGenius', indicating practical experience with LLMs, vector databases (Qdrant, ChromaDB), and orchestration frameworks (Langchain, Llama CPP).
Demonstrated ability to build and deploy machine learning applications, including web apps ('HaSa') and APIs ('RAGenius', 'textly-drf-api'), showcasing full-stack ML development capabilities.
Strong Python programming skills, which is central to the Data Scientist role, with practical application in numerous deep learning and NLP projects.
Experience with MLOps related tools like Dockerfile for containerization, suggesting an understanding of deployment and reproducibility.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's personal projects demonstrate a strong passion for advanced AI/ML topics, particularly in generative models and natural language processing. The projects align well with a research-oriented or innovative Data Scientist role. The breadth of technologies used (PyTorch, Langchain, Docker, various vector DBs) indicates adaptability and a willingness to explore new tools. The current role as a Data Scientist at Extreme Networks, although with a future start date, suggests alignment with industry expectations for the role. However, the lack of team-based projects or collaborative work descriptions makes it difficult to fully assess cultural fit in a team environment.

Soft Skills & Operational Fit

The candidate's project descriptions are clear and concise, indicating good written communication. The diversity of projects, particularly in advanced AI/ML domains, suggests a proactive and self-driven individual. However, without psychometric or English test results, a comprehensive assessment of soft skills, logical reasoning, work attitude, stress handling, and team collaboration is not possible.

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Projects

RAGenius

October 26, 2025 – November 13, 2025

🧠 RAGenius: Production-ready Retrieval-Augmented Generation API built with FastAPI, Azure OpenAI, and ChromaDB. Supports multi-format document processing, streaming responses, and incremental vector store updates.

View Project

Medical-RAG-LLM

February 22, 2024 – February 22, 2024

This project implements a RAG (Retrieval-Augmented Generation) system using an open-source stack. It utilizes BioMistral 7B as the main model along with other technologies such as PubMedBert for embedding, Qdrant for a self-hosted Vector DB, and Langchain & Llama CPP for orchestration frameworks.

View Project

Enhanced-Super-Resolution-GAN

June 8, 2021 – May 11, 2022

This is the PyTorch implementation of ESRGAN .

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Super-Resolution-GAN

June 4, 2021 – June 7, 2021

This is PyTorch implementation of SRGAN from scratch.

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Convolutional-Variational-Autoencoder

May 14, 2021 – May 14, 2021

PyTorch implementation of Variational Autoencoder.

View Project

Cycle-GAN

March 27, 2021 – June 7, 2021

This is a PyTorch implementation of Cycle GAN from Scratch.

View Project

Pix2Pix-Conditional-GANs

March 13, 2021 – June 16, 2021

This is the PyTorch implementation of Pix2Pix Paper.

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textly-drf-api

January 17, 2021 – January 25, 2021

All-in-one API for grammar correction, spell check, sentiment analysis,Text Summary,Text Generation, Neural Machine Translation

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AR-Drone

October 15, 2020 – October 15, 2020

An Augmented Reality Drone made with Unity and AR foundation.

View Project

HaSa

August 22, 2020 – October 16, 2024

A Depression Text Detector - A Machine Learning Web App

View Project

Key Strengths

Extensive experience with various Generative Adversarial Networks (GANs) including Pix2Pix, ESRGAN, Cycle-GAN, and SRGAN, demonstrating strong foundational knowledge in deep learning for image generation and enhancement.
Proficiency in Retrieval-Augmented Generation (RAG) systems, as evidenced by projects like 'Medical-RAG-LLM' and 'RAGenius', indicating practical experience with LLMs, vector databases (Qdrant, ChromaDB), and orchestration frameworks (Langchain, Llama CPP).
Demonstrated ability to build and deploy machine learning applications, including web apps ('HaSa') and APIs ('RAGenius', 'textly-drf-api'), showcasing full-stack ML development capabilities.
Strong Python programming skills, which is central to the Data Scientist role, with practical application in numerous deep learning and NLP projects.
Experience with MLOps related tools like Dockerfile for containerization, suggesting an understanding of deployment and reproducibility.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Mohd Aquib

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit