Research Engineer/Scientist - Speech/Audio Machine Learning

Institute of Foundation Models; Paris; Presencial; EUR 90 000 - 150 000; Tempo integral

Resumo da oferta

The Institute Of Foundation Models in Paris is seeking a Research Scientist specializing in speech/audio machine learning to contribute to the design and training of state-of-the-art end-to-end neural speech models.

You will focus on developing core IP, moving beyond cascaded ASR→TTS toward native audio-to-audio multimodal architectures, collaborating with researchers, data scientists and engineers.

Qualificações

• PhD or MSc in Computer Science with a focus on Deep Learning, Signal Processing, or Computational Linguistics.
• Record of Research: Published work in top-tier venues (NeurIPS, ICLR, ICASSP, Interspeech).

Responsabilidades

• Architectural Design: Develop novel neural architectures for low-latency speech-to-speech translation and generation (e.g., Diffusion, Flow-matching, Transformer-based audio LLMs).
• Loss Function Engineering: Design and implement custom objective functions to optimize prosody (emotions, intelligibility, naturalness).
• Experimental Iteration: Conduct large-scale training runs, performing ablation studies on model architecture and tokenization strategies.
• Evaluation Frameworks: Establish rigorous internal benchmarks using both objective metrics (WER, MCD) and subjective human-in-the-loop (MOS) testing.

Conhecimentos

Speech/audio ML

Research publication track record

Formação académica

PhD or MSc in Computer Science (Deep Learning / Signal Processing / Computational Linguistics)

Descrição da oferta de emprego

About The Institute Of Foundation Models

We are a dedicated research lab for building, understanding, using, and risk-managing foundation models. Our mandate is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy.

As part of our team, you’ll have the opportunity to work on the core of cutting-edge foundation model training, alongside world-class researchers, data scientists, and engineers, tackling the most fundamental and impactful challenges in AI development. You will participate in the development of groundbreaking AI solutions that have the potential to reshape entire industries. Strategic and innovative problem-solving skills will be instrumental in establishing MBZUAI as a global hub for high-performance computing in deep learning, driving impactful discoveries that inspire the next generation of AI pioneers.

The Role

As a Research Scientist specializing in speech/audio machine learning, you will contribute to the design and training of SoTA end-to-end neural speech models. You will be responsible for developing the core intellectual property, moving beyond cascaded ASR → TTS systems toward native audio-to-audio multimodal architectures.

Key Responsibilities

• Architectural Design: Develop novel neural architectures for low-latency speech-to-speech translation and generation (e.g., Diffusion, Flow-matching, Transformer-based audio LLMs).
• Loss Function Engineering: Design and implement custom objective functions to optimize prosody (emotions, intelligibility, naturalness).
• Experimental Iteration: Conduct large-scale training runs, performing ablation studies on model architecture and tokenization strategies.
• Evaluation Frameworks: Establish rigorous internal benchmarks using both objective metrics (WER, MCD) and subjective human-in-the-loop (MOS) testing.

Qualifications

• PhD or MSc in Computer Science with a focus on Deep Learning, Signal Processing, or Computational Linguistics.
• Record of Research: Published work in top-tier venues (NeurIPS, ICLR, ICASSP, Interspeech).

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.