Daniel Cárdenas

AI Automation Engineer: RAG · Edge ML · Firmware

I build practical AI systems: RAG pipelines, voice and document automation, Python APIs, and the embedded telemetry that makes edge ML useful in the real world.

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AI automation with hardware-level instincts.

I build production-oriented AI systems across documents, business workflows, and connected devices. My recent work includes RAG pipelines for clinical simulation workflows, a Gemini-powered Telegram inventory bot, and smart-meter NILM systems that connect STM32 acquisition, Python services, MQTT telemetry, and field devices.

I am strongest where software has to touch reality: noisy sensor data, private documents, legacy spreadsheets, uncertain prompts, and users who need the system to work without drama. My toolkit spans Python/FastAPI/Flask, Postgres/pgvector/FAISS, Gemini/Azure OpenAI, Docker, STM32/FreeRTOS, and practical dashboards.

Currently

Artificial Intelligence Engineer at Lean Tech; previously ML/Firmware Engineer at Solenium and Machine Learning Engineer at Magnus.

Focus Areas
  • RAG, retrieval quality, and citation-aware LLM workflows.
  • Voice/document automation using Python APIs and LLMs.
  • Edge ML and smart-meter telemetry with OTA safety.
Languages
  • SpanishNative
  • EnglishProfessional
  • PortugueseProfessional
Stack Overview

Embedded

  • STM32
  • FreeRTOS
  • C/C++
  • OTA

Backend

  • Python
  • FastAPI
  • Flask
  • Postgres
  • Docker

AI

  • RAG
  • Gemini
  • Azure OpenAI
  • pgvector
  • LLM Eval

Web

  • Next.js
  • Vue
  • PyQt6
  • Dashboards