Machine Learning Scientist

Transcense Inc
Paris, France
17 days ago
Apply on startup.jobs
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Machine Learning Language Modeling Speech Recognition Deep Learning

Job description

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.

Requirements

  • 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.

Benefits & conditions

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.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on startup.jobs
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

4:20 min

Combating human workforce shortages with specialized language models

Markus Hacker Markus Hacker +3 · World Congress 2024

1:25 min

Distinguishing artificial intelligence from deep learning

Sam Witteveen · Coffee With Developers

2:36 min

Applying supervised machine learning for practical rule extraction

Katja Träumner

1:32 min

Predicting missing words using specialized language models

David vonThenen David vonThenen · World Congress 2026 Europe

3:51 min

Overcoming hardware configuration barriers in machine learning

Jose Luis Latorre Millas · LIVE

1:45 min

Introduction to serving large language models locally

Patrick Koss Patrick Koss · World Congress 2025

Videos

See all

Related articles

See all