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 Bangalore ATG team is looking for a talented, self-motivated Research Intern to investigate and develop machine learning technologies for auditory modeling. You will design, implement, and evaluate the machine learning algorithm with a good knowledge of machine learning, signal processing and basic knowledge of speech or audio processing.
This position will be in the Dolby Bangalore office, reporting to Senior AI Researcher. You are required to come to the office at least 3 out of 5 working days per week.
Essential Job Functions:
- Perform literature survey on existing methods.
- Ideate multiple potential solutions.
- Generate data required for the task.
- Develop appropriate models for the task.
- Implement ideas, generate test cases, and check performance of models on the test case.
- Document and present the methodology of experiments, methods developed, and results.
- PhD or post-doc candidate in Computer Science, Electrical Engineering, Mathematics and Computing.
- Strong knowledge of deep learning, machine learning, signal processing, linear algebra, probability and statistics.
- Experience in Python, Numpy, PyTorch, Bash scripting, and Linux terminal commands.
- One or more published papers in well-established conferences or journals.
- Good communication skills for collaboration.