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danialrp/README.md

Danial Panah

Senior AI / Machine Learning Engineer

Website LinkedIn Email


I build AI systems that run in production. The last year and a half went into an LLM-driven anomaly detection pipeline on live crypto market data (Anthropic Claude API, Go, NATS JetStream, TimescaleDB) that replaced manual review, and my own AI job-application platform with multi-provider model routing and pgvector semantic caching. Underneath that sit 10+ years of backend engineering: event-driven microservices, real-time systems, multi-tenant SaaS.

Day to day I work across LLM applications, agentic and tool-calling systems, RAG, fine-tuning with LoRA/QLoRA, and the MLOps that keeps models serving.


What I work with

LLM & Agents

LangChain LangGraph LlamaIndex MCP OpenAI API Anthropic Claude API Azure OpenAI AWS Bedrock OpenRouter

RAG & Vector Search

pgvector Qdrant Pinecone Weaviate Hybrid Search

ML & Fine-Tuning

PyTorch Hugging Face LoRA/QLoRA scikit-learn

MLOps & Cloud

Docker Kubernetes GitHub Actions AWS Azure MLflow vLLM FastAPI OpenTelemetry Prometheus Grafana

Data & Backend

Python Go TypeScript PostgreSQL TimescaleDB Redis NATS JetStream WebSockets

Daily tooling

Claude Code Cursor GitHub Copilot


Projects

Anthropic Claude API · Go · NATS JetStream · Redis · TimescaleDB · WebSockets · Docker

LLM-driven pipeline that detects anomalies and patterns in real-time crypto market data and replaced manual review. It runs on a 4-service event-driven platform: an 8-stream NATS JetStream topology, a pub/sub WebSocket layer for concurrent clients, Redis split across 4 databases (caching, aggregation state, rate limiting, connection tracking), and TimescaleDB for time-series persistence.

FastAPI · HTMX · Postgres 16 + pgvector · Redis · Docker · Chrome extension

Ingests job postings and drafts tailored resumes and screening answers, every claim traced back to a structured profile; a human reviews and submits each application. LLM calls go through OpenRouter across three model tiers with automatic fallback and hard daily and monthly budget caps. A 3-layer cache (exact match, pgvector embeddings, provider prompt cache) keeps cost down. The Chrome extension captures postings and pre-fills forms; login and final submission stay manual by design.

Earlier backend work

  • Subke CRM & Logistics Platform: multi-tenant enterprise CRM with database-driven runtime RBAC, real-time messaging hub, QR-code parcel tracking and JTL ERP integration. 30+ domain service classes across 72+ migrations, delivered with AI-assisted development alongside hand-written code.
  • websocket-server-market-streamer: Node.js/TypeScript relay that subscribes once to upstream Binance streams and re-broadcasts normalised market data to downstream clients, with Redis catch-up caching.
  • Bryant Dental: e-commerce platform for a UK dental equipment manufacturer. Awwwards Honorable Mention 2018, Dental Industry Awards Best Website 2019.

Open source

Repository
aimeos/aimeos-headless Merged PR · API-first headless e-commerce for Laravel (2.4k stars)

GitHub stats

 

danialrp.com: full portfolio, projects and CV

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  1. real-time-cryptocurrency-market-data real-time-cryptocurrency-market-data Public

    Crypto Market Data Streamer and Analyzer

    Go

  2. websocket-server-market-streamer websocket-server-market-streamer Public

    Websocket Market Data Streamer From Providers Socket Streams For Cryptocurrency Exchange Platforms Written in NodeJs and TypeScript

    TypeScript

  3. aimeos/aimeos-headless aimeos/aimeos-headless Public

    Aimeos cloud-native, API-first ecommerce headless distribution based on Laravel for ultra fast online shops, scalable marketplaces, complex B2B applications and #gigacommerce

    JavaScript 2.6k 27

  4. aegis aegis Public

    Aegis Deployer

    Go 1

  5. crypto-battlefield crypto-battlefield Public

    Live HyperLiquid order books rendered as a 1700s battle — bulls vs bears, driven entirely by market data. Three.js + Node, single container.

    JavaScript