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rehan243/README.md

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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.

Real World Applications Of Reinforcement Learning

Real World Applications Of Reinforcement Learning
2026-06-10

Real Time Data Streams For Ml Model Training

Real Time Data Streams For Ml Model Training
2026-06-09

Fine Tuning Open Source Llms For Proprietary Use C

Fine Tuning Open Source Llms For Proprietary Use C
2026-06-07

Automated Evaluation And Monitoring Of Llms In Pro

Automated Evaluation And Monitoring Of Llms In Pro
2026-06-07

📚 View all articles →


recent activity

💬 Commented on Client.embed(texts=[]) raises IndexError instead of handling in cohere-ai/cohere-python (2026-06-12)

💬 Commented on Proposal: dynamic/lazy resources/list (and directory-read) b in modelcontextprotocol/go-sdk (2026-06-12)

⭐ Starred aws-samples/sample-genai-on-eks-starter-kit (2026-06-12)

💬 Commented on Feature request: use MCP tasks extension to stream ground_lo in mapbox/mcp-server (2026-06-10)

💬 Commented on AgentThreatBench: OWASP Agentic Top 10 benchmark for indirec in openai/evals (2026-06-10)

💬 Commented on OAuth-Based Authentication for Managed MLflow Backends in zenml-io/zenml (2026-06-10)

💬 Commented on [FR]: Support OPIK_TRACK_DISABLE in Typescript SDK in comet-ml/opik (2026-06-10)

💬 Commented on [BUG/Help] <title>一加载python就崩溃 in zai-org/ChatGLM-6B (2026-06-10)


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.

🔬 Causal Inference and Discovery in Observational Data

🔬 Real-World Applications of Reinforcement Learning from Human Feedback

🔬 Real-Time Data Streams for ML Model Training

🔬 Automated Evaluation and Monitoring of LLMs in Production

🔬 Fine-Tuning Open-Source LLMs for Proprietary Use Cases

🔬 Real-Time AI Inference Optimization


code snippets

📌 Real-Time Feature Store Client — Production Pattern (Python) (2026-06-12)

📌 Agent Tool Registry with Dynamic Discovery — Production Pattern (Python) (2026-06-09)

📌 Structured Output Validator for JSON Schema — Production Pattern (Python) (2026-06-08)

🤖 Profile auto-updated on 2026-06-12 20:18 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