Hi, I'm Mohammed Musthaq, a Microsoft Certified Azure AI ML Engineer with over 7 years of experience in building and deploying AI and machine learning solutions. I specialize in developing production-grade AI systems, including Generative AI and deep learning models, primarily using Azure cloud services. I’m passionate about integrating AI into business workflows to help organizations achieve scalable, reliable, and high-performance results. Throughout my career, I’ve worked across industries such as healthcare, life sciences, and market research, where I have helped enhance model effectiveness and streamline AI development workflows. I enjoy collaborating with cross-functional teams to deliver AI solutions that simplify decision-making and drive meaningful impact.…

Mohammed Musthaq

Hi, I'm Mohammed Musthaq, a Microsoft Certified Azure AI ML Engineer with over 7 years of experience in building and deploying AI and machine learning solutions. I specialize in developing production-grade AI systems, including Generative AI and deep learning models, primarily using Azure cloud services. I’m passionate about integrating AI into business workflows to help organizations achieve scalable, reliable, and high-performance results. Throughout my career, I’ve worked across industries such as healthcare, life sciences, and market research, where I have helped enhance model effectiveness and streamline AI development workflows. I enjoy collaborating with cross-functional teams to deliver AI solutions that simplify decision-making and drive meaningful impact.…

Available to hire

Hi, I’m Mohammed Musthaq, a Microsoft Certified Azure AI ML Engineer with over 7 years of experience in building and deploying AI and machine learning solutions. I specialize in developing production-grade AI systems, including Generative AI and deep learning models, primarily using Azure cloud services. I’m passionate about integrating AI into business workflows to help organizations achieve scalable, reliable, and high-performance results.

Throughout my career, I’ve worked across industries such as healthcare, life sciences, and market research, where I have helped enhance model effectiveness and streamline AI development workflows. I enjoy collaborating with cross-functional teams to deliver AI solutions that simplify decision-making and drive meaningful impact.

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Skills

Experience Level

Azure
Expert
Data Science
Expert
Python
Expert
PyTorch
Expert
SQL
Expert
TensorFlow
Expert
GitHub
Expert
Microsoft Certified Professional
Expert
Docker
Intermediate
Jira
Intermediate
Spark
Intermediate
.NET
Intermediate
C#
Intermediate
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Work Experience

Sr AI Engineer - Sr Associate Projects at Cognizant Technology Solutions India
June 30, 2025 - August 1, 2025
Built an enterprise-grade AI chat assistant using Retrieval-Augmented Generation (RAG) to provide context-aware insights from internal market research documents. Orchestrated seamless integration of multiple APIs and services using Langchain to streamline communication and data flow. Developed interactive user interface for querying knowledge repositories with source citations, reducing market research time by 85%. Developed and deployed an innovative churn predictive model in Azure ML, improving recall and F1-score from 45% to 82%, leading to significant cost savings and customer retention. Automated model inference and monitoring pipelines and communicated complex model insights to stakeholders, resulting in increased response rates for multichannel engagement.
Data Scientist - Applications Programmer II at Black Knight India Pvt ltd
October 31, 2021 - August 1, 2025
Developed language models with spaCy to extract named entities and built text classification and sentiment analysis models. Conducted detailed text preprocessing including tokenization, stop-word removal, stemming, and lemmatization. Used TF-IDF for feature extraction and evaluated models with precision, recall, F1-score, and confusion matrix metrics to ensure accuracy.
Data Scientist at Cognerium Robotic Labs Pvt Ltd
November 30, 2019 - August 1, 2025
Developed predictive and regression models for credit risk assessment and Expected Credit Loss calculation. Built time series forecasting models, customer segmentation strategies, propensity models, and product recommendation systems, delivering actionable insights via dashboards for stakeholders.
DotNet Developer at An-nabasys Technology Solutions
November 30, 2016 - August 1, 2025

Education

Bachelor of Engineering at Osmania University, Hyderabad, India
January 1, 2008 - December 31, 2012

Qualifications

Bachelor's
January 11, 2030 - August 1, 2025
Master’s
January 11, 2030 - August 1, 2025
Microsoft Certified Azure Data Scientist
January 11, 2030 - August 1, 2025
Microsoft Certified Azure AI ML Engineer
January 11, 2030 - August 1, 2025

Industry Experience

Software & Internet, Computers & Electronics, Professional Services, Government, Healthcare, Life Sciences, Financial Services
    paper RAG System

    UAE Legal AI: GenAI RAG System

    Overview
    Production-ready Retrieval-Augmented Generation (RAG) system tailored for UAE legal documents. Built with FastAPI, Qdrant, Supabase, SentenceTransformers & Groq. Deployed on GCP N2 VM with a modular architecture and public demo interface.
    Key Features

    Semantic Chunking with Metadata Enrichment: Enhanced parsing of legal documents with meaningful context and metadata
    Hybrid Retrieval Strategy: Combines Dense, Sparse (BM25), and Late Interaction (ColBERTv2) techniques, followed by LLM-based reranking for accurate results.
    Retrieval Evaluation: MRR@10, nDCG@10, Recall@10
    LLM Response Evaluation (Human-in-the-Loop): validation of LLM responses via curated Q&A sets
    Query Translation & Chat History: Handles vague queries and follow-up questions
    Inline Citations: Each LLM response includes links to exact PDF chunks for transparency
    Realtime Logging: Logs all RAG data, scores, responses to Supabase
    Public REST APIs: Upload, Delete, and Query documents via REST APIs
    LLM Fallbacks & Retries: Implements exponential backoff, retries on rate-limits (429), and graceful fallback messaging.
    Dynamic LLM Selection: Frontend supports switching between LLMs; currently uses Groq-hosted models for cost-free inference
    Document Management: Upload, Delete and View only embedded(processed) documents
    Access Control: Upload/Delete APIs restricted to authorized users only

    Tech Stack
    FastAPI, Qdrant, Supabase, SentenceTransformers, Groq, GCP, Python, React-Typescript, TailwindCSS

    Live Demo
    https://www.twine.net/signin

    Contact
    Email: https://www.twine.net/signin
    Phone:https://www.twine.net/signin