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Senior Machine Learning Engineer (Voice Agents)

Hugging Face

Skills

Required

  • inference
  • streaming / WebSockets / WebRTC / audio or video pipelines / live inference
  • open-source
  • async
  • streaming protocol
  • session lifecycle
  • authentication
  • LLMs / multimodal models in production
  • building developer-facing infrastructure
  • APIs
  • agent infrastructure
  • Python

Preferred

  • Agents / Vocode / TEN
  • Audio pipeline
  • VAD
  • echo cancellation
  • jitter buffers
  • barge-in and turn detection
  • TTS
  • ASR / end-to-end speech models
  • speech-to-speech
  • speech-to-speech pipeline design

Join Hugging Face, a leading AI company, as a Senior Machine Learning Engineer specializing in voice agents. In this role, you will take architectural ownership of our open-source library for real-time voice agents and our new product, hf-voice. You will design the developer API, build the serving side, and support existing deployments. This position offers a flexible work environment, health insurance, unlimited PTO, equity, and opportunities for growth and training.

Motivated by voice and conversational AI

Contributions to llama.cpp or another low-level inference runtime

About Hugging Face

If you're interested in joining us, but don't tick every box above, we still encourage you to apply! We're building a diverse team whose skills, experiences, and backgrounds complement one another. We're happy to consider where you might be able to make the biggest impact

GPU serving, quantization, or on-device inference experience

Responsibilities

  • Architectural ownership of large parts of speech-to-speech pipeline design, latency budget, and reliability of the realtime loop.
  • Integration of new ASR, TTS, and end-to-end speech models, while keeping the abstractions clean.

A public track record: talks, blog posts, demos

  • Hands-on work with ASR, TTS or end-to-end speech models, including evaluation of latency and quality trade-offs
  • Contributions to a voice-agent framework such as speech-to-speech, pipecat, LiveKit Agents, Vocode or TEN

Requirements

  • Designing the developer API and the streaming protocol, including session lifecycle, transport, authentication, and error semantics.
  • Practical experience with LLMs or multimodal models in production. Clear written communication and a habit of collaborating async and in public
  • You have shipped something realtime: streaming, WebSockets or WebRTC, audio or video pipelines, live inference
  • Experience building developer-facing infrastructure at an AI or developer-tools company: inference APIs, agent infrastructure, or something comparable
  • Senior engineer, able to own a substantial part of an architecture and drive it forward autonomously
  • Substantial open-source contributions to a Python library. Comfortable with async Python and distributed systems, including their failure modes
  • Experience shipping to embedded or robotics targets

Preferred

  • Audio pipeline knowledge: VAD, echo cancellation, jitter buffers, barge-in and turn detection