---
title: "Khamar Uz Zama - Machine Learning Engineer in Hyderabad | Tal"
description: "Meet Khamar Uz Zama, Building Agentic RAG @ Amgen || Lead Machine Learning Engineer || Master’s in Data Science || +91 996 385 0007 based in Hyderabad. AI stack includes claude code, openai, and ChatGPT. Explore public work links including github and leetcode."
image: "https://tal.club/meet/khamar-uz-zama/share-image"
---

# Khamar Uz Zama on Tal

## Headline

Building Agentic RAG @ Amgen \|\| Lead Machine Learning Engineer \|\| Master’s in Data Science \|\| \+91 996 385 0007

## About

As a Data Scientist I apply my skills in Python and data science to develop and improve solutions that are secure, scalable, and user\-friendly\. I graduated with a master's degree in Data and Knowledge Engineering from Otto\-von\-Guericke University Magdeburg in Dec 2021, where I wrote my thesis on a novel method to detect liver fibrosis using heartbeat as excitation mechanism\. I have over 6 years of work experience in data science, data analytics, and research, working with various domains, such as telecommunications, environmental science, Automotive, Automation and Pharma\. I am passionate about finding innovative ways to leverage data and knowledge to solve real\-world problems and create value\.

## Location

Hyderabad

## AI stack

claude code

openai

ChatGPT

## Work experience

Machine Learning Engineer at Amgen, Dec 2024 \- Present · 1 yr 9 mos, Hyderabad, Telangana, India, Pipeline GPT: An LLM based chat that enables querying organization’s internal data directly within OpenAI’s ChatGPT • Designed and built an end\-to\-end Retrieval\-Augmented Generation \(RAG\) pipeline, ingesting data from external APIs, chunking, transformation, and generating synthetic data to be indexed into the Databricks vector store\. • Developed scalable vector ingestion jobs using PySpark and implemented Databricks Mosaic AI Vector Search to enable enterprise\-grade semantic search and retrieval\. • Created prompt\-tuned instances of CustomGPT and integrated with Databricks vector store endpoints\. • Collaborated with OpenAI and Databricks support teams to troubleshoot and resolve enterprise integration challenges, including domain authorization mismatches and performance optimization\. • Led the transition from traditional Databricks vector\-store\-based RAG to Model Context Protocol \(MCP\)\- based RAG to address token limitations, improve accuracy and reduce hallucination\. • Architected MCP tools with Pydantic models and output parsers to guarantee consistency across all the MCP tools domain while mentoring other developers on design and implementation\. • Developed MCP TestBench, an internal GenAI evaluation tool developed using DeepEval to evaluate the application performance\. • Integrated MCP TestBench into GitLab’s CICD pipeline to evaluate merge requests before merging any code into the application repository\. • Supported deployment teams during rollout, ensuring smooth releases, secure connectivity between components, and improved overall system reliability\. • Improved deployment stability by debugging MCP client \- server communication issues, optimizing Kubernetes pod allocation, and hardening MCP client configurations against network interruptions\. • Implemented a multi Agent Text2Sql that can dynamically translate natural language query to SQL, validate, execute and analyze the result using Langgraph\.

Data Scientist at Fortuna Identity, Feb 2022 \- Dec 2024 · 2 yrs 11 mos, Hyderabad, Telangana, India, EzyBot \- Visual Automation Tool • Fine\-tuned YOLOv8 Image Segmentation on UI elements dataset to detect UI elements on the screen for EZYBot\. • Worked on image processing algorithms using OpenCV and Google OCR, resulting in a surface automation tool named EZYBot that reduced automation script development time by 80% and eliminated coding completely\. EzyBot LLM Assistant • Developing an LLM Framework that can breakdown given tasks into subtasks and resolve them by making accurate API calls from given EzyBot OpenAPI specification using LangChain\. • The framework consisted of multiple agents working together like API Planner, API argument parser, API Caller and API response parser\. • Developed LLM functionality to automatically fill global parameters needed for making API calls while prompting the user if data is not present\. • Automatically makes requests to safe APIs while gets a confirmation from the user before making requests to sensitive APIs • Added memory functionality to remember users' chat history across multiple sessions\. • Implemented output parsing to verify the correctness of the received responses\. • Integrated LangSmith for tracing LLM requests and performance analytics\. • Added a RAG based feature using Croma vector DB to resolve queries of Bot Developers from multiple documentations, PDFs, and manuals • Upgraded the LLM assistant from LangChain to CrewAI framework to make it more robust and resilient to queries by introducing a Manager Agent and changing the process from sequential to hierarchical\. Data Analysis and Machine Learning Projects • Devised ETL pipelines to preprocess datasets, ensuring data quality and compatibility\. • Created insightful visualizations of graph data using Gephi, aiding interpretation of complex clusters in the graphs\. • Executed projects on Hidden Markov Models \(HMMs\) and LSTM networks for sequence predictions\. • Deployed models as endpoints via Amazon SageMaker on AWS, created RESTful microservices using Python Flask\.

Computer Vision Engineer at Inka, Apr 2021 \- Jan 2022 · 10 mos, Magdeburg, Saxony\-Anhalt, Germany, Responsibilities: ● Spearheaded innovative research aimed at assessing the viability of utilizing heartbeat\-induced stimuli for staging liver fibrosis disease\. ● Implemented the objectives of research using U\-Net Encoder\-Decoder \(Deep Neural Networks\) model for Image Segmentation and OpenCV optical flow methods for image processing in Python\. ● Validated the hypothesis of the research and authored Master’s Thesis as an integral component of my academic journey\.

Data Analyst at T\-Systems International GmbH, Oct 2020 \- Mar 2021 · 6 mos, Berlin, Germany, Responsibilities: ● Devised a use case aimed at enhancing public transport through the utilization of the International DataSpace \(IDS\) Connector\. ● Constructed a functional web application prototype employing Python Flask, JavaScript, and OpenStreetMaps integrated with the Connector for the proposed use case\. ● Implemented an advanced Named Entity Recognition \(NER\) model for the identification of source and destination locations within speech data, leveraging Natural Language Processing \(NLP\) techniques for the prototype\. ● Procured relevant data by effectively communicating the significance of the use case to key representatives from over 3 mobility startups, including Tier and Voi\.

Research Assistant at UFZ, Sep 2020 \- Oct 2020 · 2 mos, Halle, Saxony\-Anhalt, Germany, Responsibilities: ● Quantified water basin precipitation across the United States and South America through a meticulous analysis of last 75 years of historical data sourced from the MOPEX dataset\. ● Developed interactive Jupyter Notebooks to effectively visualize water basins in both the US and SA, utilizing shape files\. Constructed predictive models aimed at accurately estimating rainfall patterns\. ● Employed these notebooks to create a comprehensive visualization of time series data, subsequently utilizing mathematical computations provided by a PhD researcher to distinguish flood and drought\-prone basins\.

Member Technical Staff at CDK Global, Jun 2017 \- Dec 2018 · 1 y 6 mo, Hyderabad

## Education

Master's degree, Data and Knowledge Engineering \- Informatics/Computer Science, Otto\-von\-Guericke University Magdeburg

Bachelor of Technology \(B\.Tech\.\), Computer Science, Mahatma Gandhi Institute of technology

## Public links

- github: https://github\.com/Khamar\-Uz\-Zama
- leetcode: https://leetcode\.com/UzZama

[View the original profile](https://tal.club/meet/khamar-uz-zama)

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