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Liquid AI in the United States is seeking a hands-on Developer Relations leader to be the technical voice for small-model and edge AI communities. You will ship reference apps and tutorials, engage with developers across editorial and community channels, and craft content that demonstrates practical LLM deployment.
Sitting in Marketing & Communications, you will collaborate with model, platform, and product teams to explain work clearly, build open-source resources, and host events that
Spun out of MIT CSAIL, we build general‑purpose AI systems that run efficiently across deployment targets, from data center accelerators to on‑device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there.
Developers do not yet grasp what a fine‑tuned small model can do until they see one running on a phone, in a browser, or on a Jetson board. Closing that imagination gap is the job.
You will be Liquid’s technical voice where builders already are — Hugging Face, GitHub, Discord, and the developer events that matter for edge AI — turning individual troubleshooting sessions on chat templates, quantization, and on‑device deployment into cookbooks, reference apps, and content the whole community can use.
This is a hands‑on developer relations role focused on building, writing, and engaging publicly. You will ship reference applications and technical resources, communicate regularly with developers across editorial and community channels, and help establish a credible, consistent developer voice for Liquid.
Sitting within Marketing & Communications, you will work closely with our model, platform, and product teams. Technical teams will partner on accuracy, while you will own how the work is explained, presented, and adapted for developer audiences.
We need someone who is a:
Be the technical voice in the community. Live where LFM developers already are — Hugging Face, GitHub, Discord, X. Answer hard questions in public, maintain Liquid’s presence on the Hub, and amplify the community fine‑tunes and edge deployments worth seeing.
Show up in person. Host hackathons, build nights, and technical workshops at Liquid offices and partner venues. Represent Liquid at the conferences and developer events that matter for small‑model and edge AI — submitting talks, running booths, and demoing in the hallway track. Partner with hackathon organizers to make LFMs the obvious choice for builders who care about latency, on‑device, or cost.
Build the on‑device and adaptation story. Ship reference applications that demonstrate LFMs on real edge hardware (iOS, Android, browser, Jetson, NPUs). Maintain integration recipes for the inference stacks developers use (llama.cpp, MLX, ONNX, executorch, LEAP SDK). Write cookbooks that take a developer from base model to fine‑tuned, quantized, deployed in one sitting.
Create content that earns trust. Deeply technical blog posts, demos, and honest benchmarks against Qwen, Gemma, Phi, and SmolLM. First‑principles, concrete, no LLM slop. Turn the best in‑person workshop material into evergreen content so the in‑room audience compounds online.
Close the loop. Maintain a friction log of developer pain points — chat templates, tokenizers, deployment gotchas — and bring the signal into roadmap conversations with the model and platform teams.