Dolby Laboratories

Senior Foundational AI Researcher

Dolby seeks a Senior AI Researcher with expertise in deep learning, audio processing, and a strong publication record. Experience with generative models, self-supervised learning, and multi-modal learning is essential. You'll develop new AI solutions, enhance existing applications, and transfer technology to product groups.

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 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 is looking for a talented AI Researcher to join Dolby’s research efforts to develop the next generation of AI based audio and video technologies. You will work with Dolby’s world-class audio and vision experts to invent new multimedia analysis, processing and rendering technologies. As a part of a global team, the Senior Staff Research Engineer will work on ideas exploring new horizons in audio processing, analysis, replay and organization. You will be responsible for performing fundamental new research, transferring technology to product groups, and draft patent applications. Summary You will push the boundaries of the state-of-the-art in audio and media technologies. The 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. With the explosion of large language models and natural language processing, you will partner closely with Dolby’s worldwide AI research staff, which actively pursues the integration of such models into audio and media experiences. You will be able 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. Consequently, knowledge or experience in any/all of the following are helpful: <ul><li>Diffusion, autoregressive, or other generative models.</li><li>Natural Language Processing, LLMs.</li><li>Self-supervised, contrastive learning, auto-encoders.</li><li>Audio, image, or text applications – Source separation, text-to-speech, music synthesis, image segmentation, image captioning, question answering, language models, etc. </li></ul>
Main Responsibilities <ul><li>Partner closely with other domain experts to refine and execute Dolby’s technical strategy in artificial intelligence and machine learning.</li><li>Use deep learning to create new solutions (including foundation models) and enhance existing applications.</li><li>Push the state-of-the-art and develop intellectual property.</li><li>Transfer technology to product groups and draft patent applications.</li><li>Advise internal leaders on recent deep learning advancements in the industry and academia to further influence research direction and business decisions. </li></ul>
Requirements <ul><li>Ph.D. in Computer Science or similar field. </li><li>A strong background in deep learning, both in terms of conceptual understanding, as well as practical experience.</li><li>Strong knowledge and interest in audio processing</li><li>Knowledge in video, or text processing is desirable.</li><li>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).</li><li>Good knowledge about current machine learning literature.</li><li>Highly skilled in Python and one or more popular deep learning frameworks (TensorFlow or PyTorch).</li><li>Ability to envision new technologies and turn them into innovative products.</li><li>Good communication and collaboration skills. </li></ul>
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