Muhammad Ghulam Jillani
LinkedIn | +92-321-1174167 | +92-321-1179584 |
Jillani
Portfolio.com | m.g.jillani123@gmail.com |
Kaggle | GitHub | Medium
Professional Summary
__________________________________________________________________________________
Senior Data Scientist and Machine Learning Engineer specializing in Generative AI, LLMs, and Autonomous AI Systems, with a proven record
of transforming SaaS and PaaS platforms through innovative enterprise AI and agentic AI solutions. Expertise in optimizing workflows,
streamlining data pipelines, and building scalable AI architectures to solve complex business challenges. Recognized as a 24x LinkedIn Top
Voice, Top 100 Global Kaggle Master, and KaggleX BIPOC Mentor, contributing to the NVIDIA Developer Program, Google Developer Group,
and AWS AI Community. Demonstrated leadership in AI-driven product innovation, LLMOps strategies, and multimodal AI, delivering impactful
results with cutting-edge technologies across industries.
Technical Skills
__________________________________________________________________________________________
Programming & Development:
•
Languages & Frameworks:
Python, Scikit-Learn, TensorFlow, Keras, PyTorch, NLTK, Hugging Face Transformers, OpenCV, FastAPI, Flask,
Streamlit.
•
Tools & Libraries:
Pandas, NumPy, Matplotlib, Plotly, Seaborn, PySpark, OpenAI API, REST APIs, GraphQL, Neo4j, Docker, GitHub Actions, CI/CD
Pipelines.
•
Database Systems:
SQL, NoSQL, Vector Databases (Pinecone, Faiss, Chroma DB).
Data Science & AI:
•
Core Skills:
Machine Learning, Deep Learning, Generative AI, LLMs (GPT, Gemini, LLaMA, Falcon,DeepSeek), Natural Language Processing (NLP),
Time Series Analysis, Model Deployment, Prompt Engineering.
•
Frameworks & Tools:
LangChain, RAG (Retrieval-Augmented Generation), LlamaIndex, LangGraph, LangGraph, PhiData, LangServer, AutoGen,
LangSmith, AutoML.
•
Applications:
AI-Driven Process Automation, Predictive Modeling, Statistical Analysis, Big Data Technologies, Data Visualization.
Cloud & MLOps:
•
Platforms:
AWS (SageMaker, Lambda, Bedrock, EC2), Azure (Azure ML, Azure AI, App Services), GCP (Vertex AI, Cloud Functions), Heroku.
•
Practices:
MLOps, LLMOps, AIOps, Cloud Machine Learning, MLflow, Orchestration Frameworks.
Management & Operations:
•
Agile Methodologies, Microservices Architecture, Business Analysis, Product Management, Team Leadership, Stakeholder Management,
Business Intelligence.
Communication & Collaboration
:
•
Strong in technical writing, effective communication, stakeholder engagement, and team collaboration, fostering a productive and inclusive
environment.
Languages
:
•
Fluent in English and Urdu.
Experience
___________________________________________________________________________________________
Senior Data Scientist & Machine Learning Software Engineer (Generative AI) PURELOGICS
New York, United States
12/2024 – Currently
•
Led AI-Driven MVPs & Enterprise Deployments:
Spearheaded high-impact MVP projects, including an Enterprise-Grade RAG Pipeline for BI, a
Health Guard AI Pipeline for Remote Patient Monitoring, a GPT-4o-Based Conversational AI Chatbot, and an Agentic AI System for Legal & Financial
Advisory, leveraging Generative AI, RAG, and Autonomous AI Agents.
•
Scalable AI & Cloud Solutions:
Designed, deployed, and optimized end-to-end AI/ML pipelines on AWS (SageMaker, Bedrock, Lambda)
and GCP (Vertex AI, BigQuery, Cloud Run), ensuring high availability, cost efficiency, and real-time insights.
•
Advanced Multi-Agentic AI Architectures:
Engineered multi-agent systems with LangChain, LangGraph, PhiData, Pinecone, and Graph
DBs to enhance automation, decision-making, and autonomous AI-driven workflows across domains.
•
Leadership & Strategic Execution:
Led cross-functional teams, aligning AI strategies with business objectives, optimizing LLMOps &
MLOps pipelines, and ensuring seamless model lifecycle management from development to production.
•
Mentorship & Innovation:
Mentored AI/ML teams, fostering expertise in LLM fine-tuning, Retrieval-Augmented Generation (RAG),
and AI-powered automation, while driving continuous innovation in GenAI applications.
•
Key Achievements:
Successfully delivered scalable, enterprise-grade AI solutions, exceeding performance benchmarks, accelerating
deployment cycles, and enhancing efficiency, automation, and business intelligence.
Senior Data Scientist Machine Learning & Gen AI Engineer (Volunteer) NVIDIA
California, United States
08/2024 – Currently
•
NVIDIA & Z by HP Developer Programs:
Active member contributing to GPU-optimized applications and testing enterprise-level Generative AI
solutions on NVIDIA AI Studio and Z by HP platforms.
•
LLM Contributions:
Developed and tested open-source and enterprise-level LLMs, including vLLMs, for Generative AI domains.
•
Specialized SDK Integration:
Leveraged cutting-edge NVIDIA tools and SDKs to build and optimize AI solutions.
•
Collaborative Expertise:
Worked closely with NVIDIA and Z by HP teams to validate and enhance AI tools and frameworks.
•
Community Contributions:
Actively contributed to open-source LLM projects, driving innovation in Generative AI and large-scale deployments.
Senior Data Scientist & Machine Learning Engineer BLOCBELT
Maryland, United States
12/2022 – 12/2024
•
Strategic AI Leadership & Team Management:
Led the development of AI-driven SaaS and PaaS solutions, managing a team of three, with a
focus on Big Data, Data Analysis, and AI Engineering. This initiative enhanced operational efficiency, resulting in $2M in cost savings for clients.
•
Sales Forecasting & Market Analysis:
Improved sales forecasting accuracy by 80-90% through data analysis across 120+ market entities, leading
to actionable growth strategies and enhanced sales workflows.
•
E-Commerce Platform Innovation & Sales Growth:
Successfully launched a client-focused personalized fashion e-commerce platform featuring
an advanced recommendation engine. This initiative led to an 80% increase in sales and a 200% surge in online orders, surpassing project goals by
three months ahead of schedule.
•
Operational Excellence & Cost Reduction:
Streamlined data processing and optimized workflows using OpenCV, leading to significant cost
savings and improved efficiency.
•
Data-Driven Strategy & Revenue Growth:
Led the development of statistical models and predictive analytics, resulting in an 18% increase in
company revenue. Enhanced data visibility by 45% with strategic dashboards, fostering cross-functional collaboration.
•
AI Integration & Enhanced Digital Sales Experience:
Integrated AI into SaaS and PaaS offerings, focusing on distributed systems and conducting
over 25 A/B tests to refine the e-commerce experience, driving technological advancements.
AI Data Scientist Kaggle Master Mentor
(Part-Time, 20 hours/week)
GOOGLE-KAGGLE
San Francisco, USA
12/2022 – 11/2024
•
Championed
mentorship initiatives through the Kaggle-X BIPOC Mentorship Program, dedicating 20 hours weekly to guiding aspiring data
scientists in technical skill development and community contributions.
•
Secured
a position among the Top 100 Kaggle contributors globally, recognized as the first Pakistani mentor in the program.
•
Led
a team of four mentees, enhancing their skills in data science, machine learning, and real-world problem-solving.
•
Drove
innovation by collaborating on high-impact AI projects and actively contributing to the global data science community.
Data Scientist
Crypto-Express
Thailand
01/2022 - 12/2022
•
Developed an Anti-spoofing Face-App, enhancing digital identity security and reducing identity fraud by 70%.
•
Applied AI and ML techniques to solve industry-critical issues, improving efficiency by 25% and reducing operational costs by 15%.
•
Engineered predictive models and provided actionable insights, leading to a 20% revenue increase through data-driven decision-making.
•
Advanced expertise in EDA, Machine Learning, and Deep Learning, saving over 250+ hours of manual analysis annually.
•
Successfully deployed AI/ML projects remotely, adapting to dynamic conditions and gaining significant experience in the AI/ML field.
Artificial Intelligence Engineer
Pakistan Freelancing Training Center
Lahore, Pakistan
01/2021 - 12/2021
•
Led AI and Data Science training sessions, preparing students to tackle real-world challenges.
•
Designed
and
deployed
models
using
TensorFlow
and
Keras,
improving
system
efficiency
and
accuracy.
•
Bridged the gap between academic learning and industry skills, driving practical applications of AI technologies.
•
Automated
repetitive
data
tasks
using
Python,
significantly
reducing
manual
labor
and
error
rates.
•
Engaged
in
ongoing
AI
research
to
apply
cutting-edge
methodologies
to
projects.
Projects _____________________________________________________________________________________________
•
Health Assistance Application (LLM):
Architected a comprehensive
Health Assistance Application
leveraging the Gemini 1.5 Pro LLM model, RAG,
and LangChain. This solution supports doctors and patients by providing detailed medical information, symptom diagnosis, treatment suggestio ns,
and preventive healthcare advice. The integration of generative AI ensures accurate and personalized health recommendations, significantly
enhancing patient care and medical consultations.
•
AI-Powered Blog Generator (LLM):
Developed an AI-powered content generator leveraging Llama 3.1 8B, AWS Bedrock, and RAG for real-time fine-
tuning on dynamic datasets. Integrated with Streamlit for a seamless user interface, the system automated blog creation, editing, and publishing,
increasing efficiency in content marketing and engagement for enterprises.
•
Conversational AI Chatbot for Customer Support (GPT-4o, LangChain, Bedrock):
Designed and deployed an enterprise-grade chatbot powered by
GPT-4o, integrated with LangChain and AWS Bedrock. Implemented advanced NLP techniques such as intent recognition and dynamic response
generation, reducing customer query resolution times by 40% and improving customer satisfaction.
•
AutoML-Studio:
Built a low-code/no-code machine learning platform enabling rapid development and deployment of predictive models.
Incorporated MLflow for tracking, XAI (SHAP) for explainability, and data drift detection to ensure model reliability. Deployed with FastAPI and
Streamlit, the platform supports classification, regression, time-series forecasting and clustering, empowering non-technical users to build robust
AI solutions.
•
DocuWiz AI (LLM):
Engineered a document intelligence tool leveraging advanced NLP models like BART and DistilBERT for text extraction,
summarization, and sentiment analysis. Integrated RAG and LLMs to enable detailed insights and visualizations for PDF and DOCX analysis. Deployed
as an interactive Streamlit application and FastAPI, reducing document processing time by 60% and enhancing productivity in legal and academic
domains.
•
Harvestify-AI-Powered-Plant-Health-Assistant:
Designed and implemented an AI-driven application leveraging Azure AI Studio and Azure App
Services to diagnose plant leaf diseases through real-time image analysis. The system integrates deep learning models to recommend crops and
fertilizer solutions tailored to soil and weather conditions, enhancing agricultural decision-making. Deployed on Microsoft Azure, the solution
reduced disease detection time by 70%, improved crop yield predictions by 30%, and empowered farmers with actionable insights to optimize
productivity and sustainability.
•
Intelligent Document Summarization Tool (LLM):
Developed an Intelligent Document Summarization
Tool
using transformer-based LLM models
like Pegasus to generate concise summaries from lengthy documents while preserving key information. Deployed with FastAPI and Streamlit APP
for real-time interaction, supporting formats like PDF and DOCX, and leveraging semantic analysis for relevance extraction. Reduced manual
document review time by 60%, boosting productivity in legal and academic workflows.
•
Customer Satisfaction Prediction System (MLOps):
Created a predictive analytics system using ZenML and MLflow within an MLOps framework to
achieve 93% accuracy in forecasting customer satisfaction. Streamlined pipeline management and deployed models efficiently, providing actionable
insights that improved business decision-making and customer retention strategies.
Education
______________________________________________________________________________________________
Bachelor in Computer Science (
Major:
Artificial Intelligence and Computer Science
)
Institute of Management Sciences
CERTIFICATIONS
_________________________________________________________________________________________
•
IBM Machine Learning Specialization Professional Certificate,
IBM.
•
Deep Learning Specialization,
DeepLearning.ai.
•
Microsoft Azure AI Fundamentals AI-900 Exam Prep Specialization,
Microsoft.
•
Prompt Engineering for ChatGPT,
Vanderbilt University.
•
Machine Learning Engineering for Production (MLOps),
DeepLearning.ai.
•
AI Product Management,
Duke University.
•
Generative Adversarial Networks (GANs) Specialization,
DeepLearning.ai.
•
IBM Generative AI Product Managers,
IBM.
•
Preparing for Google Cloud Certification: Machine Learning Engineer,
Google.
•
IBM AI Product Manager,
IBM
.
•
AWS Cloud Solutions Architect Professional Certificate,
Amazon Web Services.
•
Google
Project
Management:
Professional
Certificate,
Google.
•
Practical Data Science on the AWS Cloud Specialization
, DeepLearning.ai.
•
Machine Learning Specialization,
DeepLearning.AI.
•
MLOps | Machine Learning Operations Specialization,
Duke University.
•
Google Business Intelligence Professional Certificate,
Google.
•
Advanced Machine Learning on Google Cloud Specialization,
Google Cloud.
•
Large Language Model Operations (LLMOps),
Duke University
.
•
Google Advanced Data Analytics Professional Certificate,
Google.