Building systems that think, see, and scale — fusing backend precision with production AI. Real-time surveillance meshes that identify faces in under 200 ms. Multimodal RAG pipelines digesting 1.5 lakh PDF pages at 16 pages/sec. Agentic LLM stacks that run entirely on-device, with zero API cost. Python · Django · Computer Vision · Gen AI — every day, every commit.
I'm the kind of engineer who can't sleep when a system is broken — and can't stop building when an idea clicks.
It started with a simple question: what if software could understand the world the way we do? That pulled me from basic Python scripts into training real computer vision models, building secure REST backends, and finally — systems that think, reason, and act autonomously.
My day-to-day is backend engineering in Django and Python — REST APIs, JWT auth, RBAC, N+1-free ORM queries, SSE streaming, and multiprocessing pipelines. On top of that I build the AI layer: Hybrid RAG pipelines (dense + sparse + RRF), agentic LangGraph graphs, multimodal document processors, and local LLM stacks via Ollama — all production-grade, not just demos.
In computer vision I work with YOLOv8, InsightFace ONNX, YOLO-World, Qwen-VL, and DeepFace — building real-time surveillance systems that process 10+ concurrent camera feeds, detect faces in under 200 ms, and stream alerts over SSE with MJPEG-compressed video at 60% bandwidth reduction.
I maintain a detailed public work log at AI-ML-at-Cactus-Creatives — daily notes, experiment results, architecture decisions, and every lesson learned the hard way. I commit every single day, not to fill a streak, but because I genuinely work every day.
Advanced AI-driven educational resource aggregator and personalized learning path generator.
Professional distributed AI surveillance with edge face detection and centralized neural recognition.
Silent, headless web automation tool with smart retry logic and resume support.
Production-grade multimodal RAG pipeline treating every document page as both text and image.
Robust Django CMS for dynamic content lifecycle management, featuring threaded comments and moderation.
Distributed edge-intelligence system using Flask, Pydantic-AI, and local Ollama agents.
Scalable recruitment ecosystem with three-tier RBAC and optimized database query patterns.
E2E encrypted messaging system using proprietary 3-layer bitwise XOR encryption.
Comprehensive educational resource planning system for campus management.
Fully local private AI agent routing between Wikipedia and live web search with persistent memory.
Real-time object tracking system with region-of-interest gating for optimized processing.
Interactive virtual piano controlled by real-time hand gesture recognition and skeletal tracking.
Secure biometric authentication system based on palm-vein and texture analysis.
YOLOv8 model training studio with live epoch log streaming via Server-Sent Events.
AI-powered medical report analysis and diagnostic assistance tool.
GitHub is a living journal. Every day brings new commits — features, refactors, experiments. 30+ repositories across ML pipelines, backend systems, and AI tooling.
A dedicated repo tracking real-world AI/ML work. The notes/ folder
documents daily progress, models trained, and architectural decisions.
| ✓ | Computer Vision — YOLO · OpenCV · ROI | Done |
| ✓ | RAG & Agents — Pipelines · Agentic AI | Done |
| ◕ | Transformers — HuggingFace · Fine-tuning | Active |
| ◕ | LLM Orchestration — LangChain · LangGraph | Active |
| ◕ | Gen AI — Prompt Eng · Multimodal · APIs | Active |
| ○ | MLOps — Tracking · Deployment · CI/CD | Next |
| ○ | Deep Learning — CNNs · Attention | Next |
Building open-source tools for the community — Python, Django, and ML ecosystem.
Pursuing advanced specialization in IT and Computer Applications — deepening expertise in system architecture, algorithms, and applied AI/ML methodologies.
Foundation in computer science — OOP, DBMS, web technologies, data structures, and software engineering principles that underpin all my backend work today.
Open to backend engineering, ML engineering, and AI-native development roles. Systems thinking, security-first design, and daily-commit work ethic.
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