Machine Learning Engineer 2 - Computer Vision / Audio

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

We seek a skilled Machine Learning Engineer to join our dynamic and innovative team. The ideal candidate will have a strong background in machine learning, experience with innovative ML projects, and preferably a background in startup environments. A deep understanding of Diffusion models, and hands-on experience with PyTorch Lightning, are useful.
What You'll Do

Design, develop, and implement sophisticated machine learning models to tackle complex problems.

Work on Diffusion models to improve Adobe's product offerings.

Collaborate with cross-functional teams to integrate machine learning solutions into production systems.

Optimize machine learning models for performance using PyTorch Lightning.

Conduct research to stay updated with the latest machine learning and AI advancements.

Analyze and interpret large datasets to extract significant insights.

Document and present findings and solutions to technical and non-technical collaborators.

What you need to succeed

Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, or a related field.

Prior experience in computer vision or audio is a must.

Experience in developing and deploying machine learning models.

A good understanding of Diffusion models.

Hands-on experience with PyTorch Lightning.

Proficiency in Python and machine learning libraries such as TensorFlow, Keras, or similar.

Having publications at top-tier peer-reviewed conferences or journals is a plus

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