Senior Generative AI Researcher

Key Skills

Aartificial intelligence, Decision trees, Deep Learning, Framework, Kubernetes-K8s, Large Language Models - LLMs, NeurIPS, PyTorch, TensorFlow, UI design, UX design

Job Description

Join the leader in entertainment innovation and help us design the future. At Dolby, science meets art, and high tech means more than computer code. As a member of the Dolby team, you’ll see and hear the results of your work everywhere, from movie theaters to smartphones. We continue to revolutionize how people create, deliver, and enjoy entertainment worldwide. To do that, we need the absolute best talent. We’re big enough to give you all the resources you need, and small enough so you can make a real difference and earn recognition for your work. We offer a collegial culture, challenging projects, and excellent compensation and benefits, not to mention a Flex Work approach that is truly flexible to support where, when, and how you do your best work.

Dolby’s research division is looking for an AI researcher to join Dolby’s research efforts to develop the next generation of AI based multimodal technologies. The candidate will work with Dolby’s world-class audio and vision experts to invent new multimedia analysis, processing and rendering technologies to drive new interactive and immersive experiences. As a part of an international team, the senior staff research engineer will work on ideas exploring new horizons in multimodal processing, analysis, replay and organization. The researcher is responsible for performing fundamental new research, transferring technology to product groups, and draft patent applications.

Summary

Dolby’s research division is currently looking for a talented, self-motivated AI researcher to push the boundaries of the state-of-the-art in media technologies. An ideal candidate would have a strong background in deep learning, both in terms of conceptual understanding, as well as practical experience. A core aspect of this role involves being able to keep up to date with the literature, implement, and innovate with the bleeding edge in generative models, self-supervised learning, and multi-modal learning. Consequently, knowledge or experience in any/all the following are helpful:

• Diffusion, autoregressive, or other generative models.
• Self-supervised, contrastive learning, auto-encoders.
• Audio, image, or text applications – Source separation, text-to-speech, music synthesis, image segmentation, image captioning, question answering, language models, etc.

With the explosion of large language models and natural language processing, the candidate will work closely with Dolby’s Applied AI team, which actively pursues the integration of such models into audio and media experiences. Prospective candidates would be expected to hit the ground running, innovate, and contribute to such projects. Consequently, experience with language models, question answering, vision-language models, captioning, etc. would be highly beneficial.

The role will involve prototyping inspiring experiences that explore a complement of modalities. These technologies will be used to extend immersion and interaction, so the candidate should be willing to explore empirical refinement of the user experience.

Main responsibilities:

• Work closely with other domain experts to refine and execute Dolby’s technical strategy in artificial intelligence and machine learning.
• Use deep learning to create new solutions and enhance existing applications.
• Push the state-of-the-art and develop intellectual property.
• Transfer technology to product groups and draft patent applications.
• Advise internal leaders on recent deep learning advancements in the industry and academia to further influence research direction and business decisions.
• Prototype and demonstrate multimodal, interactive and immersive user experiences.

Requirements:

• Ph.D. in computer science or similar, with a focus on deep learning. Knowledge in audio, video, or text processing is desirable.
• Strong publication record, with publications in major machine learning conferences (e.g., NeurIPS, ICLR, ICML). Publications in top domain-specific conferences is desirable (e.g., ACL, CVPR, ICASSP)
• Good knowledge about current machine learning literature.
• Exposure in LLMs, LLM planning, reasoning, and agentic AI.
• Highly skilled in Python and one or more popular deep learning frameworks (TensorFlow or PyTorch)
• Ability to envision new technologies and turn them into innovative products. Creativity
• Good communication skills.