Our team has released the Seamless Communication models at the end of 2023, the very first massively multilingual, streaming and expressive multimodal translation systems. We are looking for a Research Engineer, expert in speech generation to take these models to the next level by making them production ready. Overtime, this project will be transitioned fully to an infrastructure team, and the role will support our next research vision to build a personalizable, controllable foundation model for synchronous, multimodal and expressive behavior generation. Meta Fundamental AI Research (FAIR) is a research organization committed to advancing open AI research, and we will push the boundaries of human-centric understanding and generation. Our team's technology will enable next-generation human-to-human and human-to-machine communication.

Research Engineer, Speech Generation - FAIR Responsibilities

• Collaborate, and execute on research that pushes forward the state of the art in human-centric understanding and generation.


• Directly contribute to experiments, including designing experimental details, writing reusable code, running evaluations, and organizing results.


• Develop methodology and benchmarks to evaluate different approaches.


• Work with a large and globally distributed team.

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.


• Masters Degree in Computer Science or relevant technical field


• 3+ years of industry, academic or government laboratory experience


• Experience holding an industry, faculty, or government researcher position


• Experience developing machine learning algorithms or machine learning infrastructure in Python


• Experience writing software and executing complex experiments involving large AI models and datasets


• Experience in speech generation and text-to-speech

Preferred Qualifications

• A PhD in AI, computer science, data science, or related technical fields.


• Direct experience in generative AI, and LLM research.


• First author publications experience at peer-reviewed AI conferences (NeurIPS, CVPR, ICML, ICLR, ICCV, ACL, EMNLP, Interspeech, etc.))


• Experience in multimodal generation modeling, in particular human motion generation modeling.

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