New AI Scientist, Audio

Mistral AI Mistral AI · AI Frontier · Paris, France · Research

AI Scientist on the Audio team at Mistral AI, focused on pushing the frontier of speech-language models. Responsibilities include researching novel methods for training, evaluating, and deploying state-of-the-art AI systems, improving speech AI performance across multilingual and multimodal use cases, and contributing to AI research through publications and open-source innovation.

What you'd actually do

  1. Research and develop novel methods to push the frontier of large language models
  2. Improve speech AI performance across multilingual and multimodal use cases.
  3. Work across use cases (e.g reasoning, code, agents) and modalities (e.g text, image and speech)
  4. Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale
  5. Work cross-functionally with other scientists, engineers and product teams to ship AI systems which have a real-world impact

Skills

Required

  • Expertise in speech AI, including speech input/output and audio processing.
  • Strong software engineering skills in Python or another modern programming language.
  • Hands-on experience with AI frameworks such as PyTorch or JAX, and distributed systems such as Ray or Kubernetes.
  • Ability to design and build scalable, production-ready machine learning systems.
  • Experience training, fine-tuning, and evaluating large transformer or speech-language models.
  • Strong problem-solving skills with a proactive, self-driven approach to research and engineering.
  • Collaborative mindset with the ability to work effectively across research, engineering, and product teams.
  • Track record of contributing to AI research through publications, open-source projects, or technical innovation.

Nice to have

  • multilingual and multimodal use cases
  • reasoning, code, agents
  • text, image and speech modalities
  • tooling and infrastructure for training, evaluation and analysis of AI models at scale
  • shipping AI systems with real-world impact

What the JD emphasized

  • Expertise in speech AI
  • Track record of contributing to AI research through publications, open-source projects, or technical innovation

Other signals

  • push the frontier of speech-language models
  • novel methods for training, evaluating, and deploying state-of-the-art AI systems
  • Improve speech AI performance across multilingual and multimodal use cases
  • Contribute to AI research through publications and open-source innovation