Research Scientist, GenAI - Multimodal Audio (Speech, Sound and Music) - Meta

The GenAI org at Meta builds industry leading LLM and multimodal generative foundation models, which sets the industry benchmark of open source foundation models and enables many Meta products.The team is working on the industrial leading research on multimodal generative foundation models with a focus on the audio modality (including speech, sound and music). The team is working closely with the language and the vision research teams, and is collaborating with product teams in bringing the results to benefit billions of Meta users around the world.

RESPONSIBILITIES

Research Scientist, GenAI - Multimodal Audio (Speech, Sound and Music) Responsibilities:

• Full life-cycle research on multimodal generative foundation models with a focus on the audio modality, including bringing up ideas
• Designing and implementing models and algorithms
• Collecting and selecting training data, training / tuning / scaling the models, evaluating the performance, open sourcing and publication
• Work together with collaborating teams (e.g. language and vision) to leverage each other and deliver the high-level goals.

MINIMUM QUALIFICATIONS

Minimum Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• Solid track record of research in the audio (speech, sound, or music) or vision (image or video) domains. Can be publication records or unpublished industrial experience.
• PhD degree in the related field with 3+ years of experience, or BS degree with 5+ years of industrial research experience in the related field.
• Related research fields: audio (speech, sound, or music) generation, text-to-speech (TTS) synthesis, text-to-music generation, text-to-sound generation, speech recognition, speech / audio representation learning, vision perception, image / video generation, video-to-audio generation, audio-visual learning, audio language models, lip sync, lip movement generation / correction, lip reading, etc.
• Proven knowledge in neural networks.
• Experienced in one of the following popular ML frameworks: Pytorch, Tensorflow, JAX.
• Experienced in Python programming language.
• Solid communication skills.

PREFERRED QUALIFICATIONS

Preferred Qualifications:

• Solid publication track record in related fields.
• Solid experience in either of the following: audio dataset curation, model scaling, audio generation model evaluation.
• Experienced in large-scale data processing.
• Experienced in solving complex problems involving trade-offs, alternative solutions, cross functional collaboration, taking into account diverse points of views.