Dolby - Deep Learning Intern - Location - San Francisco, CA - 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. Summary The Rapid Prototyping Group focuses on identifying disruptive trends and technologies and creates experiences to evaluate feasibility and business viability. Responsibilities: - Participate in developing solutions for real-world problems using artificial intelligence and machine learning. - Integrate multiple technology components (audio, video) to create prototype experiences that can be evaluated to prove product viability. Qualifications: - Pursuing a Master's or Ph.D. degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field. - Hands-on experience with Deep Learning: RNNs and/or CNNs. - Familiarity with one or more neural network frameworks, such as Tensorflow, PyTorch. Preferred qualifications: - Exposure to industry or academic research. - Understanding of linear algebra, probability distribution, hyper-parameters and evaluation metrics. - Large data analysis and visualization experience. - Experience with linear algebra, calculus, and statistics Dolby will consider qualified applicants with criminal histories in a manner consistent with the requirements of San Francisco Police Code, Article 49, and Administrative Code, Article 12 Equal Employment Opportunity: Dolby is proud to be an equal opportunity employer. Our success depends on the combined skills and talents of all our employees. We are committed to making employment decisions without regard to race, religious creed, color, age, sex, sexual orientation, gender identity, national origin, religion, marital status, family status, medical condition, disability, military service, pregnancy, childbirth and related medical conditions or any other classification protected by federal, state, and local laws and ordinances. #LI-AS1