Liquid AI
AI
MemberofTechnicalStaff-DeveloperRelations
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Member of Technical Staff - Developer Relations at Liquid AI. Skills: LLMs, Developer Relations, On-device Deployment. Be the technical voice in the community. Live where LFM developers already are”
What You'll Achieve.
Ship working reference app; Developers adopt content; Ship often; Adapt quickly; Take on more ownership; Measurable lift in fine-tunes; Measurable lift in downloads; Measurable lift in downstream Spaces; External developers fork reference apps; External developers extend reference apps; External developers ship reference apps; Developer community shows up for events; Measurable community growth; Pain points are surfaced and fixed; OSS contributions land; Talks get accepted; Inbound developer interest grows
Industry & Context.
Troubleshooting sessions; Solve developer pain points
Travel for events, In-person presence at events
What They're Looking For.
Must Have
Proven technical expertise, hands-on experience with LLMs, model fine-tuning (LoRA, QLoRA, full fine-tuning, distillation), tokenizer debugging, track record of shipping to production or active community environments, Fluency with the modern AI stack, deep familiarity with PyTorch, Hugging Face (Transformers, PEFT, Datasets), model serving frameworks (llama. cpp, MLX, vLLM, ONNX Runtime, or TGI), understanding of quantization tradeoffs (GGUF, AWQ, GPTQ, INT8/INT4), Efficient model specialization, experience with on-device deployment (iOS, Android, embedded), specialized work within the efficient-model ecosystem (Phi, Gemma, Qwen, SmolLM, or distilled architectures)
Nice to Have
Prior developer relations, developer advocacy, community engineering experience, track record of public technical communication, conference talks, widely read technical writing, following among ML and edge developers, Active open-source contributions, inference or efficient-model tooling ecosystem (llama. cpp, MLX, ONNX, Hugging Face libraries), Experience organizing or running hackathons, workshops, developer events
What You'll Do.
Be the technical voice in the community
Live where LFM developers already are
Answer hard questions in public
Maintain Liquid's presence on the Hub
Amplify community fine-tunes
Represent Liquid at conferences
Demo in the hallway track
Partner with hackathon organizers
Build the on-device and adaptation story
Ship reference applications
Maintain integration recipes
Create content that earns trust
Deeply technical blog posts
Maintain a friction log
Bring signal into roadmap conversations
How You'll Work.
Team & Collaboration
Work with product team; Collaborate with model and platform teams
Communication Scope
Honest technical communicator; Public technical communication
Full Job Description
ABOUT LIQUID AI 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. THE OPPORTUNITY 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 builder role focused on shipping, not strategy: you will ship often, adapt quickly, and take on more ownership as you go. WHAT WE'RE LOOKING FOR We need someone who is a: - Builder: You would rather ship a working reference app than write a strategy memo, and you measure yourself by what developers actually adopt. - Community native: You enjoy answering hard questions in public, you are comfortable being wrong in front of people, and you know the small-model and edge-AI ecosystem well enough to have real opinions. - Honest technical communicator: You benchmark fairly, you do not oversell, and you have a low tolerance for vague or generated-sounding content. - In-person energizer: Hackathons, workshops, hallway-track demos, and the conferences where builders actually show up are where you do your best work. - End-to-end owner: You take ownership in ambiguity and turn one-off problems into reusable resources without being asked. THE WORK - Be the technical voice in the community. Live where LFM developers already are — Hugging
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