Senior Machine Learning Engineer, Voice Agents - EMEA Remote

Hugging Face
Paris
Workplace: RemoteFull timeFunction: Data Science & Machine LearningEducation: mastersSkills: ["Architectural ownership","Autonomous execution","Written communication","Collaborating async","Open-source collaboration"]

Own core parts of an open voice-agent stack by architecting and evolving Hugging Face’s realtime speech-to-speech library and integrating new ASR/TTS/end-to-end speech models. Build hf-voice by designing developer APIs and streaming protocols, delivering GPU-backed realtime inference with concurrency, autoscaling, observability, and cost controls. Take the stack from demo to production with load testing, SLOs, and reliability improvements.

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FursaFursa
Hugging Face
Hugging Face
1 week ago

Senior Machine Learning Engineer, Voice Agents - EMEA Remote

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 17 hours agoStatus: Live

Job Summary

Own core parts of an open voice-agent stack by architecting and evolving Hugging Face’s realtime speech-to-speech library and integrating new ASR/TTS/end-to-end speech models. Build hf-voice by designing developer APIs and streaming protocols, delivering GPU-backed realtime inference with concurrency, autoscaling, observability, and cost controls. Take the stack from demo to production with load testing, SLOs, and reliability improvements.
Location: Paris
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Provide architectural ownership for speech-to-speech: pipeline design, latency budget, and reliability of the realtime loop.
  • •Integrate new ASR, TTS, and end-to-end speech models while keeping abstractions clean as the model ecosystem evolves.
  • •Ship hf-voice by designing the developer API and streaming protocol, including session lifecycle, transport, authentication, error semantics, and versioning.
  • •Build the serving side for realtime inference on GPU with concurrency, autoscaling, observability, and cost per session.
  • •Take the product from demo to production using load testing, SLOs, and graceful degradation when models or network paths misbehave, while supporting the Hub/inference teams.
Travel: Low travel

Pay and Benefits

Equity and Bonus:Equity
Perks:Health InsuranceDentalVisionParental LeaveRemote WorkEquity

Key Requirements

  • •Experience building developer-facing infrastructure for AI or developer tools (e.g., inference APIs, agent infrastructure).
  • •Substantial open-source contributions to a Python library, with strong async Python and distributed-systems know-how.
  • •Have shipped realtime capabilities such as streaming, WebSockets/WebRTC, or live audio/video pipelines.
  • •Practical experience with LLMs or multimodal models in production and the ability to collaborate asynchronously and in public with clear written communication.
  • •Motivation and interest in voice and conversational AI, with hands-on understanding of voice-agent components.
Experience:AIDeveloper toolsOpen sourceDistributed systemsLLMsMultimodal modelsReal-time inference
Education:Master's
Skills:Architectural ownershipAutonomous executionWritten communicationCollaborating asyncOpen-source collaboration
Tech Stack:PythonAsync PythonDistributed systemsASRTTSSpeech-to-speechEnd-to-end speech modelsWebSocketsWebRTCGPURealtime inferenceAutoscalingObservabilityLLMsMultimodal modelsLatency budgetLoad testingSLOsStreaming protocolSession lifecycle

Company Brief

Hugging Face
Builds open-source tools, models, and a platform for machine learning and natural language processing, enabling developers and organizations to train, deploy, and share AI models and datasets.
Industry: AI & Machine Learning
Company Size: Enterprise (1,001+ employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series C
Headquarters: New York, United States
Founded: 2016
WebsiteLinkedIn