Applied ML Engineer, Voice agents

Make our voice agents better at the hardest conversations in healthcare: hold music, IVRs, accents, interruptions and a receptionist having a bad day.

• Improve ASR robustness on real telephony audio; build the hold/IVR/voicemail classifiers.
• Design conversation policies as explicit state machines with LLM-generated turns, and evaluate them offline and online.
• Build the eval suite: transcripts, outcomes, specialist labels. Own the metrics.
• Ship weekly. Listen to the calls.

• Experience with speech systems in production (ASR, TTS, or dialogue).
• Strong Python and PyTorch; comfortable with data pipelines and evals.
• You can read a transcript and know why the call failed.

Four steps, two weeks if you want it that fast. A 30-minute call with the hiring manager. A practical exercise related to the role (paid, if it takes more than two hours). A half-day with the team, in person or remote, including a session listening to real retrieval calls. Then references and an offer.

• Meaningful equity at a seed-stage company
• Full health coverage for you and dependents
• Paris and Boston offices, or remote within EU / US time zones
• Six weeks' leave, plus local public holidays
• Annual learning budget, hardware of your choice, relocation support