James Ray Email & Phone Number | Pioneer in Generative AI, focused on applied research and product development to augment human creativity and empower artists. ML/AI product leader with extensive experience formulating deep learning models for practical applications. Partnering with Academy Award and Emmy-winning film directors and technologists. Currently implementing generative algorithms and other forms of creative ML to meet the needs of filmmakers and game developers. -- My personal mission is to honor and elevate human creativity and art direction, through a combination of artist-centric design and AI. At Netflix, I lead the development of deep learning, graphics/simulation, and imaging products to advance studio production, visual effects/Post, and imaging technology. I have the privilege to work with filmmakers and artists as we unlock new modes of creative expression with AI, together. Before Netflix, I led Twitter's computer vision products and product strategy, including direct partnership with the CTO. There, I led media understanding to promote the public conversation. Part of this role was recommending content that sparks engagement, inspiration and curiosity. To do that, we used multi-modal AI to understand images, video, audio, and language holistically - closer to the way humans do. I also led R&D on generative AI for content creation. Prior to Twitter, I spent time as an engineering manager and in executive leadership. On the eng side, I worked hands-on with SWEs and researchers (eg, implementing and productizing one of the earliest interactive GANs). I also spent time partnering directly with Fortune 100 C-suites to guide their most critical tech investments. Outside the day job, I've been a technical advisor to AI startups in pioneering domains, like spatiotemporal deep learning for brain-computer interfaces, and presented at ML conferences (e.g., on deep reinforcement learning). Selected past work: --Partnering with artists to formulate creative workflows - maximizing the expressiveness of generative AI to augment human creativity --Interactive generative adversarial networks (GAN) for AI-augmented creative design --Multi-modal embeddings for recommending, ranking, and search algorithms (computer vision, NLP, and graph embeddings, factorization machines, learning-to-rank) --Human pose estimation, action recognition, and emotion detection from live video --Spatiotemporal deep learning for signal processing, video classification, and brain-computer interfaces --State-of-the-art speech and natural language processing for virtual agents

James Ray

Pioneer in Generative AI, focused on applied research and product development to augment human creat...
Los Angeles, California, United States

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James Ray’s Email jray@netflix.com

James Ray’s Phone Numbers +1 877-421-****

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James Ray’s Location Los Angeles, California, United States

James Ray’s Current Industry Netflix

James Ray’s Prior Industry Twitter | Deloitte Consulting | Blue Altair | Accenture

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Work Experience

Netflix

AI Product Manager - Media Algorithms (VFX/Animation/Games/Film) + Generative AI initiative leader

2021-09-01T00:00:00.000Z - Present

Twitter

Staff Product Manager - Media Understanding (ML/AI)

2021-02-01T00:00:00.000Z - 2021-09-01T00:00:00.000Z

Deloitte Consulting

Global Lead - Computer Vision | Head of Deep Learning Research + GPM | Senior Engineering Manager

2019-04-01T00:00:00.000Z - 2021-02-01T00:00:00.000Z

Blue Altair

Director of Product (AI); Director of Engineering (Global Leadership Team)

2017-01-01T00:00:00.000Z - 2019-04-01T00:00:00.000Z

Accenture

Product Leader (ML Platforms, Algorithms), Engagement Lead (Data Science, Strategy), Data Scientist

2010-08-01T00:00:00.000Z - 2017-01-01T00:00:00.000Z

Skills

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Languages

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FAQ About James Ray

James Ray is located at
Los Angeles, California, United States

James Ray is a Pioneer in Generative AI, focused on applied research and product development to augment human creativity and empower artists. ML/AI product leader with extensive experience formulating deep learning models for practical applications. Partnering with Academy Award and Emmy-winning film directors and technologists. Currently implementing generative algorithms and other forms of creative ML to meet the needs of filmmakers and game developers. -- My personal mission is to honor and elevate human creativity and art direction, through a combination of artist-centric design and AI. At Netflix, I lead the development of deep learning, graphics/simulation, and imaging products to advance studio production, visual effects/Post, and imaging technology. I have the privilege to work with filmmakers and artists as we unlock new modes of creative expression with AI, together. Before Netflix, I led Twitter's computer vision products and product strategy, including direct partnership with the CTO. There, I led media understanding to promote the public conversation. Part of this role was recommending content that sparks engagement, inspiration and curiosity. To do that, we used multi-modal AI to understand images, video, audio, and language holistically - closer to the way humans do. I also led R&D on generative AI for content creation. Prior to Twitter, I spent time as an engineering manager and in executive leadership. On the eng side, I worked hands-on with SWEs and researchers (eg, implementing and productizing one of the earliest interactive GANs). I also spent time partnering directly with Fortune 100 C-suites to guide their most critical tech investments. Outside the day job, I've been a technical advisor to AI startups in pioneering domains, like spatiotemporal deep learning for brain-computer interfaces, and presented at ML conferences (e.g., on deep reinforcement learning). Selected past work: --Partnering with artists to formulate creative workflows - maximizing the expressiveness of generative AI to augment human creativity --Interactive generative adversarial networks (GAN) for AI-augmented creative design --Multi-modal embeddings for recommending, ranking, and search algorithms (computer vision, NLP, and graph embeddings, factorization machines, learning-to-rank) --Human pose estimation, action recognition, and emotion detection from live video --Spatiotemporal deep learning for signal processing, video classification, and brain-computer interfaces --State-of-the-art speech and natural language processing for virtual agents