500+ Users in 1st Month
Since launch.
Parampreet Singh
Parampreet Singh
Parampreet Singh
ResumeBased in India
ResumeI am an AI/ML Engineer specialized in building production-grade AI systems. Currently, I'm focused on finetuning Small Language Models (SLMs) and scaling Gurmat Darbar, a full-stack platform for the Sikh community.
Educator at heart, I've delivered 70+ live sessions on Python and ML to 100K+ learners.
My work sits at the intersection of deep learning applications & scalable backend architecture.
BS in Data Science and Applications, IIT Madras (2022-Present)
LLMs, Mathematical Foundations for GenAI, and Software Engineering.
Building the biggest digital ecosystem for the Sikh community.
Lead & engineered a Full-Stack platform to solve event discovery and data fragmentation using modern AI pipelines.
500+ Users in 1st Month
Since launch.
Largest Sikhi Samagam Platform
Covered 150+ Samagams with 200+ contributions.
Biggest Curated Sikhi Database
Structured multilingual data extraction.
Architecture focused on multilingual data extraction and auto-poster generation.


Gurmat Darbar
Sept 2025 – Present
Built a Full-Stack platform for the Sikh community featuring 'Find Samagams Near Me', covering 150+ Samagams with 200+ contributions.
Engineered a GenAI pipeline for structured multilingual data extraction and auto-poster generation.
mPragati Lab, IIT Delhi
Sept 2025 – Present
Working on 3D skull implant generation using deep learning for biomedical reconstruction.
Creating and training 3D U-Net based architectures for skull implant reconstruction.
Coridors
Aug 2024 – Sep 2025
Built a Streamlit-based data ingestion platform with 30+ interactive screens integrated with Snowflake.
Worked on backend integrations with Snowflake Snowpark for scalable data workflows.
Designed, deployed, and maintained the company website using JavaScript and Tailwind CSS via Vercel and Cloudflare.
YouTube (@Param3021)
Jan 2023 – Present
Delivered 70+ live sessions on Python and ML, reaching 100K+ learners.
Python, machine learning, revision marathons, and the kind of teaching that turns exam fear into momentum.



Parampreet Singh
@Param3021
Subscribers: 3.92k
Covers full Python - Basic to Advanced, full Machine Learning, Revision sessions, Course guidance, project guidance videos.
175K+
Learners
Concept-first teaching that helps learners move from basics to confidence.
70+
Live Sessions
Regular live sessions covering Python, Machine Learning, and revision support.
500+
Student Feedbacks
Real learner appreciation from doubt-solving, project guidance, and mentorship.
Wall of Love

A lightning-fast, 1.2B parameter local AI coding assistant designed to run flawlessly on CPUs and GPUs. Fine-tuned on a custom code-instruction dataset, it acts as a fully offline, zero-latency copilot inside Jupyter Notebooks and VS Code, completely bypassing cloud APIs.
Jupyter %%code Magic Command
VS Code MCP Server Integration

A production-grade, multi-agent GenAI platform that autonomously generates highly personalized GitHub READMEs. Orchestrated using LangGraph, it features three specialized AI agents working in tandem. The system utilizes real-time Server-Sent Events (SSE) for fluid streaming and is deployed securely on GCP Cloud Run.
LangGraph Agent Orchestration
100+ Unique Users in 16 Hours

An exploratory deep learning research project implementing Liquid Neural Networks (LNNs) to handle 32-dimensional continuous-time motion data. By building custom Liquid Time-Constant (LTC) cells from scratch, the architecture improved temporal adaptability and significantly outperformed standard LSTMs.
Custom Liquid Time-Constant Cells
+9.6% Accuracy vs standard LSTM

A highly scalable, full-stack quiz management platform engineered with a robust asynchronous backend. It utilizes Redis and Celery for distributed background task queues to handle concurrent user loads, automating complex workflows like API rate limiting and dynamic certificate generation.
Redis & Celery Task Queues
Automated Email & Certificates
Contact
I am open to AI engineering collaborations, product-focused builds, speaking, and research-driven projects.