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.
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Advanced Technology Group (ATG) is the research and technology arm of Dolby Labs. It has multiple competencies that innovate technologies in audio, video, AR/VR, gaming, music, and movies. Many areas of expertise related to computer science and electrical engineering, such as AI/ML, computer vision, image processing, algorithms, digital signal processing, audio engineering, data science & analytics, distributed systems, cloud, edge & mobile computing, natural language processing, knowledge engineering and management, social network analysis, computer graphics, image & signal compression, computer networking, IoT are highly relevant to our research.
Currently, Dolby India ATG team is looking for a talented, self-motivated Research Intern to investigate and develop foundational model. You will design, implement, and evaluate the multi-modality models that requires good knowledge of fundamental deep learning concepts, multi-modality architectures, representation learning, and basic knowledge of vision, audio, and text processing.
This position will be in the Dolby India office (Bangalore), reporting to Senior Director. You are required to come to the office 3 working days per week.
Essential Job Functions:
- Develop novel and state-of-art multi-modality architectures focused on representation learning
- Evaluate performance of developed model on different applications
- Document and present the methodology of experiments, methods developed, and results
- Pursuing PhD (third year onwards) in Electric Engineering, Computer Science, Mathematics, Physics or similar
- Strong knowledge in more than one of the following domains:
- o Deep-learning fundamental concepts
o Self-supervised learning or representation learning
o Multi-modal architectures (Such as CLIP)
o Latent diffusion based generative models
o State-space models
- o Deep-learning fundamental concepts
- Solid programming skills in Python
- Basic knowledge of vision, audio, and text processing
- Experienced in technical writing and filing patents.
Publications in the multi-modality or generative-AI domain is a plus
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