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rehan243/README.md

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GitHub followers  LinkedIn  Kaggle  profile visitors

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about me

i'm an AI/ML engineer based in the US. right now i'm building production AI systems at Reallytics.ai and Verticiti, mostly getting large language models to do useful things in the real world. not demos, actual systems with real users and real traffic.

before this i was at Afiniti and Cloud Kinetics for a few years. fraud detection, voice analytics, enterprise search. the kind of stuff that pages you at 3am when something breaks.

honestly what keeps me going is when an agent you built solves something you never explicitly told it to do. that feeling never gets old.

what i'm working on right now:

  • multi-agent systems that don't fall apart when you chain them
  • RAG pipelines that actually return relevant results
  • writing about what i learn every day, check it out here
 coding

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featured projects  rocket

Agentic AI Workflows
8 specialized AI agents with LangChain + OpenAI function calling. multi-agent orchestration with planning loops and guardrails. the project i'm most excited about right now.

RAG Enterprise Search
production retrieval pipeline over 2TB+ data. hybrid dense+sparse search with FAISS and BM25, cross-encoder re-ranking. deployed on AWS SageMaker.

Voice AI Platform
real-time voice infrastructure handling 500+ concurrent calls. WebSockets, Kafka, VAD, streaming STT. built the sentiment analysis piece from scratch.

LLM Fine-Tuning LoRA
fine-tuning LLaMA and Mistral with LoRA/QLoRA/PEFT. 40% cheaper than hosted APIs. includes the full training loop, data pipeline, merge + quantize scripts.

RLHF LLM Optimization
full RLHF pipeline: reward model with Bradley-Terry loss, PPO trainer with KL scheduling, DPO as an alternative. 68% win rate on eval, 96% safety compliance.

Sentinel Fraud Detection
ensemble XGBoost + neural net with 650+ engineered features. Redis-backed real-time velocity scoring, SHAP explainability, Kafka alert routing.

view all repositories

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tech stack

not going to pretend i use everything equally. here's what i actually reach for:

tech stack

the full picture (click to expand)
daily drivers Python, PyTorch, FastAPI, Docker, Git, VS Code
LLM and GenAI LangChain, LlamaIndex, HuggingFace Transformers, vLLM, PEFT/LoRA/QLoRA
data and vector FAISS, ChromaDB, Pinecone, PostgreSQL, MongoDB, Redis, Kafka, Elasticsearch
cloud and MLOps AWS (SageMaker, Bedrock, Lambda, ECS), GCP Vertex AI, Azure OpenAI
ML frameworks TensorFlow, scikit-learn, XGBoost, LightGBM, ONNX
infrastructure Kubernetes, Terraform, GitHub Actions, MLflow, Weights & Biases

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github stats

github stats streak stats

top languages

trophies

trophies

contribution graph

contribution graph

my github contributions eating themselves

contribution snake

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recent writeups

i write about what i'm building and learning. nothing polished, more like notes to my future self that happen to be public.

Efficient Large Language Model Deployment

Efficient Large Language Model Deployment
2026-05-24

 Automl For Computer Vision

Automl For Computer Vision
2026-05-23
Llm Fine Tuning At Scale With Lora

Llm Fine Tuning At Scale With Lora
2026-05-21

 Efficient Deployment Of Large Language Models

Efficient Deployment Of Large Language Models
2026-05-20

📚 View all articles →

recent activity

💬 Commented on Feature: Add MCP server trust verification before tool execu in crewAIInc/crewAI (2026-05-24)

💬 Commented on TensorArray(dynamic_size=True, size=0) inside while_loop sil in tensorflow/tensorflow (2026-05-24)

💬 Commented on 🎉 Your project is featured in awesome-ai-chat-apps in lm-sys/FastChat (2026-05-24)

💬 Commented on spacy download --url is silently ignored or rejected — the in explosion/spaCy (2026-05-24)

💬 Commented on 1.3.0rc15: trtllm-serve hangs in fused_moe/quantization.py in NVIDIA/TensorRT-LLM (2026-05-24)

💬 Commented on Add AGENTS.md — guidance for AI coding assistants contributi in guidance-ai/guidance (2026-05-23)

💬 Commented on Relax lightning <= 2.4.0 cap to allow >= 2.6.1 (security fix in NVIDIA-NeMo/NeMo (2026-05-23)

💬 Commented on [Docs]: Google Gemini Handler in mindsdb/minds-platform (2026-05-23)

what i'm reading lately

stuff i've been digging into recently. mostly papers, blog posts, and rabbit holes that kept me up too late.

🔬 Real-time Data Quality Monitoring for ML Systems

🔬 Explainable AI for Deep Learning Models

🔬 Efficient Large Language Model Deployment

🔬 Reinforcement Learning from Human Feedback (RLHF)

🔬 AutoML for Computer Vision

🔬 Synthetic Data Generation for Training Robust Models

code snippets

📌 Streaming JSON Parser for Large Language Models — Production Pattern (Python) (2026-05-24)

📌 Batch Inference Pipeline with Progress Tracking — Production Pattern (Python) (2026-05-24)

📌 Real-Time Feature Store Client — Production Pattern (Python) (2026-05-23)

🤖 Profile auto-updated on 2026-05-24 19:25 UTC

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if you made it this far, you should probably just say hi

connect on linkedin   follow on github

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  1. Voice-AI-Platform Voice-AI-Platform Public

    Real-time voice AI infrastructure — 500+ concurrent calls, WebSockets, Apache Kafka, gRPC/C++ with CUDA. Speech-to-text, sentiment analysis, sales insights.

    Python

  2. Agentic-AI-Workflows Agentic-AI-Workflows Public

    Production AI Agents for enterprise automation — 8+ specialized agents using LangChain, OpenAI function calling, and FastAPI. Multi-agent orchestration, tool use, planning loops, guardrails.

    Python

  3. BiiView-Object-Detection BiiView-Object-Detection Public

    Real-time object detection with Meta AI Segment Anything Model (SAM) — 90% accuracy across 11M+ images and 1.1B+ segmentation masks.

    Python

  4. Digital-People-Platform Digital-People-Platform Public

    Hyper-realistic talking avatars — SadTalker lip-sync + Microsoft SpeechT5 TTS + OpenAI conversational AI. 70% realism improvement.

    Python

  5. LLM-Fine-Tuning-LoRA LLM-Fine-Tuning-LoRA Public

    Fine-tuning LLaMA-2, Mistral with LoRA, QLoRA, PEFT — 40% cost reduction vs hosted APIs. VLLM serving with CUDA optimization on AWS SageMaker.

    Python

  6. RAG-Enterprise-Search RAG-Enterprise-Search Public

    Production RAG pipeline — enterprise knowledge retrieval across 2TB+ data using LangChain, FAISS, ChromaDB, PG-Vector with cross-encoder re-ranking. Deployed on AWS SageMaker.

    Python