Senior Machine Learning Engineer, Voice Agents - EMEA Remote
Salary not listed • Remote • Paris, Île-de-France, France; Remote • Full-time
Posted 1mo ago
Remote Work Policy
Fully remote
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
Hugging Face is seeking a Senior Machine Learning Engineer to lead a significant portion of their open voice-agent stack. This role focuses on two key areas: the open-source library 'speech-to-speech' for real-time voice agents, and 'hf-voice,' a new product enabling developers to build and deploy voice agents. You will take architectural ownership, integrate new models, manage community contributions, design developer APIs, build the serving infrastructure for real-time inference, and guide the product from demo to production. The position also involves creating documentation, supporting existing deployments, and potentially sharing work publicly through blog posts or conference talks.
Responsibilities
- Take architectural ownership of the speech-to-speech library, including pipeline design, latency budgets, and real-time loop reliability.
- Integrate new ASR, TTS, and end-to-end speech models while maintaining clean abstractions.
- Review community pull requests, triage issues, manage releases, and foster contributor growth for the open-source project.
- Design the developer API and streaming protocol for hf-voice, covering session lifecycle, transport, authentication, and versioning.
- Build the serving infrastructure for hf-voice, focusing on real-time GPU inference, concurrency, autoscaling, observability, and cost management.
- Collaborate with Hub and inference teams to ensure seamless integration of voice agents into products and demos.
- Manage the transition of hf-voice from demo to production, including load testing, SLOs, and graceful degradation strategies.
- Create documentation, examples, and templates to facilitate developer adoption of voice agents.
- Support existing deployments utilizing the voice agent stack, such as the Reachy Mini fleet.
- Communicate technical work publicly through blog posts, demos, or conference talks.
Requirements
- Senior engineering experience with the ability to autonomously own and drive architectural components.
- Experience building developer-facing infrastructure in AI or developer-tools companies, such as inference APIs or agent infrastructure.
- Substantial open-source contributions to a Python library.
- Proficiency in asynchronous Python and distributed systems, including understanding failure modes.
- Shipped real-time systems, such as streaming, WebSockets, WebRTC, audio/video pipelines, or live inference.
- Practical experience deploying LLMs or multimodal models in production.
- Clear written communication skills and experience with asynchronous and public collaboration.
- Motivation for voice and conversational AI.
Benefits
- Reimbursement for relevant conferences, training, and education.
- Flexible working hours and remote options.
- Health, dental, and vision benefits for employees and dependents.
- Parental leave and flexible paid time off.
- Opportunity to visit office spaces in NYC and Paris.
- Workstation outfitting to ensure success.
- Company equity as part of the compensation package.
- Support for the ML/AI community.