Dolby is looking to drive innovation in multimodal AI for audio applications, multimodal representations, and generative modeling for audio, speech, and music to create new experiences and push the boundaries of sound and multimedia experiences.
Requirements
- Generative modeling for audio applications (diffusion models, autoregressive models, masked generative transformers).
- Multimodal semantic understanding and multimodal reasoning.
- Multimodal representations (audio-video, audio-text, audio-video-text).
- Multimodal AI architectures, with a focus on generating audio, music, and speech (text-to-audio, video-to-audio, image-to-audio).
- Self and semi-supervised learning.
- AI driven audio enhancement, processing, and generation (for speech and music), such as speech enhancement and analysis, source separation, text-to-speech, text-to-music, music information retrieval, audio classification.
- LLMs for audio applications.
Responsibilities
- Use deep learning to create new solutions (including foundation models) and enhance existing applications.
- Push the state-of-the-art and develop intellectual property.
- Transfer technology to product groups.
- Establish research collaborations with external university partners.
- Mentor interns on novel research problems.
- Publish papers in top-tier conferences and journals.
- Advise internal leaders on recent deep learning advancements in the industry and academia to further influence research direction and business decisions.
Other
- Ph.D. in Computer Science or similar field.
- Deep passion for audio, music, and multimedia applications.
- Strong publication record, with publications in major machine learning conferences (e.g. NeurIPS, ICLR, ICML) or top domain-specific conferences is desirable (e.g., ACL, CVPR, ICASSP, Interspeech).
- Ability to envision new technologies and turn them into innovative products.
- Good communication and collaboration skills.
