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Hugging Face

Senior Machine Learning Engineer, Voice Agents

Hugging Face

Senior machine learning engineer owning Hugging Face’s speech-to-speech library and hf-voice platform. Building realtime GPU inference and developer-facing voice-agent infrastructure.

Posted 9/3/2026full-timeRemote • 🇫🇷 FranceSeniorWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in architecting and developing speech-to-speech systems, with a strong focus on real-time performance, developer-facing infrastructure, and open-source contributions. Proficient in integrating advanced speech models and optimizing GPU inference for production environments.

Highest-signal resume keywords
Architecture OwnershipReal-Time Systems DevelopmentOpen-Source ContributionsAsync Python and Distributed SystemsDeveloper-Facing Infrastructure

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
ASRTTSEnd-to-End Speech ModelsGPU ServingQuantizationOn-Device InferenceAudio Pipeline KnowledgeLatency EvaluationStreaming Protocol DesignWebSockets
Soft Skills
Clear Written CommunicationCollaboration
Tools & Technologies
WebRTCInference APIsVoice-Agent FrameworksLlama.cppPipecatLiveKit AgentsVocodeTEN
Industry Keywords
Voice AIConversational AIEmbedded SystemsRoboticsCommunity Contributions

Tech Stack

Tools & technologies
Distributed SystemsPython

About the role

Key responsibilities & impact
  • Own architecture for substantial parts of the speech-to-speech open-source library, including pipeline design, latency budget, and realtime-loop reliability
  • Integrate new ASR, TTS, and end-to-end speech models while maintaining clean abstractions
  • Review community pull requests, triage issues, cut releases, and grow project contributors
  • Design the hf-voice developer API and streaming protocol, including session lifecycle, WebSockets/WebRTC transport, authentication, error semantics, and versioning
  • Build realtime GPU inference serving with concurrency, autoscaling, observability, and cost-per-session optimization
  • Collaborate with Hub and inference teams to simplify voice-agent integration into products and demos
  • Take hf-voice from demo to production through load testing, SLOs, and graceful degradation
  • Write documentation, examples, and templates for developers
  • Support existing deployments, beginning with the Reachy Mini fleet
  • Publicly discuss the work through blog posts, demos, or conference talks

Requirements

What you’ll need
  • Senior engineer able to own a substantial part of an architecture and drive it forward autonomously
  • Experience building developer-facing infrastructure at an AI or developer-tools company, including inference APIs or agent infrastructure
  • Substantial open-source contributions to a Python library
  • Comfortable with async Python and distributed systems, including their failure modes
  • Experience shipping realtime systems involving streaming, WebSockets, WebRTC, audio or video pipelines, or live inference
  • Practical production experience with LLMs or multimodal models
  • Clear written communication and ability to collaborate asynchronously and publicly
  • Motivation by voice and conversational AI
  • Contributions to voice-agent frameworks such as speech-to-speech, Pipecat, LiveKit Agents, Vocode, or TEN
  • Contributions to llama.cpp or another low-level inference runtime
  • Hands-on experience with ASR, TTS, or end-to-end speech models, including latency and quality trade-off evaluation
  • GPU serving, quantization, or on-device inference experience
  • Audio pipeline knowledge including VAD, echo cancellation, jitter buffers, barge-in, and turn detection
  • Experience shipping to embedded or robotics targets
  • Public track record through talks, blog posts, or demos

Benefits

Comp & perks
  • Diversity, equity, and inclusivity-focused workplace
  • Equal opportunity employer and nondiscrimination commitment
  • Reimbursement for relevant conferences, training, and education
  • Flexible working hours
  • Remote work options
  • Health, dental, and vision benefits for employees and dependents
  • Parental leave
  • Flexible paid time off
  • Opportunity for remote employees to visit NYC and Paris offices
  • Workstation equipment provided as needed
  • Company equity for all employees
  • Community supporting the ML/AI community