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The Greater Change

Senior AI Systems & Local LLM Engineer - Smart Home & Agentic AI

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeDubai - United Arab EmiratesIn-person

About the Job

Requirements

  • At least 3 years of software or AI engineering experience and a strong portfolio of deployed production systems.
  • Hands-on experience integrating custom components, local voice pipelines, or large language models into Home Assistant.
  • Exceptional speed and fluency using modern AI-assisted coding tools such as Cursor, Copilot, and Windsurf to write clean, working code.
  • Comfort operating in Linux environments, managing Proxmox hypervisors, and configuring Linux Containers and virtual machines for GPU workloads and smart home services.
  • Production-grade skills in Python and Node.js.
  • Hands-on experience with local model deployment, quantization formats such as GGUF, EXL2, and AWQ, and multi-device local compute clusters such as Exo and LMStudio.
  • Familiarity with agent orchestration paradigms, tool use, local memory storage, and frameworks such as Hermes or OpenClaw.

Responsibilities

  • Deploy, tune, and maintain self-hosted large language model setups using tools such as LMStudio, Exo, vLLM, and Ollama, and integrate locally trained or fine-tuned model weights into production environments.
  • Design and connect autonomous AI agents using frameworks such as OpenClaw, Hermes, and custom agentic graphs; build real-time voice agents and interactive AI avatars.
  • Integrate local AI voice agents and agentic control layers into Home Assistant for low-latency, privacy-focused automation and interactive control.
  • Build resilient middleware that dynamically routes queries between high-throughput local models and frontier APIs such as OpenAI, Anthropic, and Gemini.
  • Provision, manage, and optimize enterprise compute nodes using Linux, including Ubuntu and Debian, and Proxmox VE; handle GPU passthrough, container orchestration, and resource allocation.
  • Develop high-concurrency backend services, real-time streaming endpoints using WebSockets or Server-Sent Events, and API layers using Python frameworks and libraries including FastAPI and AsyncIO, and Node.js.

Desired Qualifications

  • Experience with IoT communication protocols such as MQTT, Matter, and Zigbee, including Zigbee2MQTT or ZHA.
  • Experience fine-tuning local models using tools such as Unsloth, QLoRA, and Axolotl.
  • Familiarity with real-time audio pipeline tools such as WebRTC, Deepgram, and ElevenLabs, and local text-to-speech and speech-to-text stacks such as Whisper, Piper, and XTTS.
  • Active homelabber or self-hosting enthusiast with real-world experience managing physical or virtual GPU rigs and smart home setups.

About the Company

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