Mohammed Shuaib Iqbal
Machine Learning Engineer @EY
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WORK HISTORY
Machine Learning Engineer @EY
Architected a memory-efficient distributed LLM fine-tuning framework using QLoRA and TorchRun, enabling 7B+ parameter models to run on commoditymulti-GPU nodes and reducing infrastructure costs by 40–60%. Engineered multi-node distributed training pipelines on GCP, optimizing throughput via batch size tuning and data loading strategies for large-scale datasets (200K+ samples). Architected an LLM-powered Brand Compliance Agent system using LangGraph, RAG pipelines, and vector databases to automatically evaluate influencer video transcripts and marketing assets against brand guidelines, deployed via FastAPI APIs, Azure serverless functions, and containerized Docker infrastructure. Architected a multi-agent healthcare assistant using LangGraph and FastAPI with a supervisor-driven orchestration pattern that routes user intents to specialized agents handling appointment booking, cancellation, and rescheduling via PostgreSQL, while combining RAG over hospital knowledge (Markdown) and DuckDuckGo search for trusted medical information retrieval.
EDUCATION
University Visvesvaraya College of Engineering
M.E, Power and Energy Systems
Internshala Trainings
Placement Guarantee Course , Data Science
University Visvesvaraya College of Engineering ( UVCE )
Master of Engineering, Energy Management and Systems Technology/Technician
RNSIT-Official
Bachelor of Engineering, Electrical and Electronics Engineering
Trainity
Data Analytics
iNeuron.ai
Machine Learning Masters
ABOUT MOHAMMED SHUAIB IQBAL
Hi, I am Mohammed Shuaib Iqbal. A Data Analytics/Scientist Enthusiast, turning Data into meaningful Information to help business solve their problems.During my M.E. I have done 3 months of internship at ABB and I have done a project in my Master\'s which was published at Conference, Journal, and recognized my paper by many scholars for their project work.\"Multiple Contingency Analysis for optimal placement and estimate the value of SVC for power loss reduction employing Particle Swarm Optimization.Published in: 2019 4th International Conference on Electrical, Electronics, Communication, Computer Technologies and Optimization Techniques (ICEECCOT)\".The reason to move to Data Science is, as I have always been passionate about Mathematics, Statistics and have a keen interest in understanding and solving complex business problems. I have also sought education to further build on my interests and implement whatever I have learned.My abilities as a data scientist are built, tested, and improved upon by the Data Science Specialization offered by Internshala Trainings. During this extensive program, I learned Advanced Excel, Python, SQL, Machine learning, and Tableau through lectures, live projects, regular vivas, and live classes. The course has been designed and monitored by Analytics Vidhya, one of the best educators in analytics education.I spent my days working on extensive problems, e.g, Taxi scheduling & fare problems for a cab service firm, Predictive analytics on a dataset for FIFA19, and File handling and String Manipulation using Python. Did well in the test and Projects that are conducted by Internshala Trainings.I Have gained Data Analytics Certificate from Trainity completing 7 projects in SQL and Advance Excel.1. Instagram User Analytics(SQL)2. Operations & Metric Analytics(SQL)3. Hiring Data Analysis4. IMDB Movie Analysis5. Bank Loan Case Study6. XYZ Ads Airing Analysis7. ABC Call Volume Trend AnalysisUp for a talk?Find myself fit for a role?Reach me at i••••••••@gmail.com
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