Senior Machine Learning Engineer, Voice Agents - EMEA Remote

<p>At Hugging Face, we're on a journey to democratize good AI. We are building the fastest growing platform for AI builders with over 11 million users who collectively shared over 3M+ models, 1M+ datasets &amp; 1.47M+ apps. Our open-source libraries have more than 600k+ stars on Github.</p><p></p><p><strong>About the Role</strong></p><p>We are building the open voice-agent stack for Hugging Face, and we are looking for a senior engineer to own a large part of it.Two things sit at the centre of this role. The first is <a href="https://github.com/huggingface/speech-to-speech" rel="nofollow noreferrer noopener" class="external">speech-to-speech</a>, our open-source library for realtime voice agents. The second is hf-voice, a new product that will let any developer build and deploy voice agents with their Hugging Face account.&nbsp;</p><p>The library already powers the Reachy Mini fleet and there is a <a href="https://huggingface.co/spaces/smolagents/hf-realtime-voice" rel="nofollow noreferrer noopener" class="external">public demo</a> running on Spaces, so you won't start from a blank page. But almost everything about how this becomes a product developers rely on is still open, and you will have a direct say in it.</p><p></p><p><strong>Your missions:</strong></p><p><strong>- Own the Open-Source Library:</strong></p><ul><li>Take architectural ownership of large parts of speech-to-speech: pipeline design, latency budget, and the reliability of the realtime loop.</li><li>Integrate new ASR, TTS and end-to-end speech models as they land, and keep the abstractions clean while the model landscape keeps moving.</li><li>Review community PRs, triage issues, cut releases, and grow the group of contributors around the project.</li></ul><p></p><p><strong>- Ship hf-voice: </strong></p><ul><li>Design the developer API and the streaming protocol: session lifecycle, transport (WebSockets/WebRTC), authentication, error semantics, versioning.</li><li>Build the serving side: realtime inference on GPU, concurrency, autoscaling, observability, and cost per session.</li><li>Work with the Hub and inference teams so that a working voice agent is easy to integrate into products and demos.</li><li>Take the product from demo to production: load testing, SLOs, graceful degradation when a model or a network path misbehaves.</li></ul><p><strong>- Work in the Open: </strong></p><ul><li>Write the docs, examples and templates that get a developer from zero to a running agent in minutes.</li><li>Support the deployments already relying on the stack, starting with the Reachy Mini fleet.</li><li>Talk about the work publicly if you enjoy it: blog posts, demos, conference talks. We cover the travel and the prep time.</li></ul>