> Markdown version of [/jobs/ext/2726660-machine-learning-scientist](https://www.wearedevelopers.com/jobs/ext/2726660-machine-learning-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Scientist - **Company:** Transcense Inc - **Location:** Paris, France - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Machine Learning, Language Modeling, Speech Recognition, Deep Learning - **Published:** September 5, 2026 - **Apply:** https://startup.jobs/machine-learning-scientist-ava-8168758 ## About the Role * 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. ## 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. ## Related Videos - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Fireside Chat: Deep Learning, Deep Impact: Harnessing AI for Language Innovation](https://www.wearedevelopers.com/videos/612-fireside-chat-deep-learning-deep-impact-harnessing-ai-for-language-innovation) - [Unveiling the Magic: Scaling Large Language Models to Serve Millions](https://www.wearedevelopers.com/videos/1619-unveiling-the-magic-scaling-large-language-models-to-serve-millions) - [Inside the Mind of an LLM](https://www.wearedevelopers.com/videos/1617-inside-the-mind-of-an-llm) - [Graphs and RAGs Everywhere... But What Are They? - Andreas Kollegger - Neo4j](https://www.wearedevelopers.com/videos/1311-graphs-and-rags-everywhere-but-what-are-they-andreas-kollegger-neo4j) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)