Machine Learning Engineer - Firefly Video

Our Company Changing the world through digital experiences is what Adobe's all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We're passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.

We're on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

The Opportunity

• Design and train the next generation video and multi-modal generation models
• Collaborate closely with Researchers and Machine Learning engineers to incorporate the latest innovations and experimental features
• Collaborate closely with product partners to define features and joint shipping objectives, and work towards them
• Lead projects from scoping requirements to launch, ensuring ongoing support
• Lead a project with multiple teams of researchers and engineers
• Stay updated with the latest test, development, and deployment practices, and actively share knowledge with the team and community

What you need to succeed:

• Master's degree or above in Computer Science or a related field, or equivalent practical experience
• Solid foundation in computer science fundamentals
• Strong proficiency with deep learning models: architecture, training, evaluation, optimization and deployment. Especially with generative models e.g transformers, diffusion models
• Strong proficiency in Python and PyTorch, working with large and complex code-bases
• Experience working on machine-learning projects, excellent communication and collaboration skills
• Think creatively about troubleshooting, debugging, and solving complex, hard-to-reproduce problems

Nice to have:

• Experience in shipping ML models to consumers: scaling up models for inference, working with product teams to integrate models, maintaining models in production

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