Machine Learning Scientist
Paris, IDF, France
- Pay
- Pay not listed
- Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingDevelop real-time voice recognition that works in real-world conversations
Work on source localization, microphone calibration and source separation
Process signals from ad-hoc microphone arrays to tell who says what
From the employer’s posting
reinvent what voice recognition can do to understand real-world conversations
source localization, voice recognition, microphone calibration, speech recognition, source separation
The signal is acquired via an array of ad-hoc microphones, and is processed to guess who says what
What you’ll bring
All qualificationsCore experience
- More than 3 years of research experience in machine learning, including deep learning
Preferred experience
- Experience in speaker identification, ASR, NLP, acoustic or language modeling, or source separation
Qualification wording
You have > 3 years of research experience in Machine Learning (including Deep Learning).
Experience in Speaker Identification, ASR, NLP, acoustic modeling, language models or source separation is a plus.
Posting record
Report an errorOpen 4 monthsWe first saw this posting 121 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jul 3, 2026 · 121 days ago
- Recorded sightings
- 36
- Last seen by us
- Oct 31, 2026
- Employer says posted
- Feb 15, 2020
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
Description du poste
What you'll be doing:
The core of your mission will be to reinvent what voice recognition can do to understand real-world conversations: crack the cocktail-party problem.
The signal is acquired via an array of ad-hoc microphones, and is processed to guess who says what, using a set of techniques: source localization, voice recognition, microphone calibration, speech recognition, source separation… all in real-time.
What we offer:
- An opportunity to apply cutting-edge technologies to solve real world problems, right now.
- Empowering and fast-paced working environment.
- Competitive salary and equity opportunity.
- The job will be based in our Paris office.
Qualifications
- You have > 3 years of research experience in Machine Learning (including Deep Learning).
- Experience in Speaker Identification, ASR, NLP, acoustic modeling, language models or source separation is a plus.
- You ambition to be a pioneer in the field, and do what is necessary to make things work in real world situations.
- You're of the persistent, yet open-minded and collaborative type: you reason by independent thinking first, but you know that together, we're stronger.
Informations supplémentaires
All your information will be kept confidential according to EEO guidelines.
Description de l'entreprise
We want to radically improve how we humans communicate with each other. Our first step at Ava is to empower 450M deaf and hard-of-hearing people to live in a fully accessible world.
Every day, millions of people are excluded from conversations because they cannot hear what others say well. Our CEO Thibault grew up in a Deaf family & witnessed firsthand how the world was not accessible for them. Together with our CTO Skinner — deaf since age 2 — Thibault co-founded Ava to make live captioning of conversations as easy as turning on captions on TV.
Our small but fast-growing team has reinvented AI-based speech recognition technology to be in service of people who need it the most. We dream of a 24/7 accessible world, without any communication barrier.
In this pursuit, we're seeing how critical communication skills are, yet very far from ideal, to unleash our collective potential. This is for us the last barrier to be lifted.
Our belief is that well-designed technology can help everyone communicate and connect better — much more effectively and authentically — so humanity can achieve the greatest things together.
We want to make the seemingly impossible equation of collaboration 1 + 1 = 3, work every time. In other words, make 1 & 1 = 3 a reality.
Source details
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Paris, IDF, France
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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