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
Develop ML models, platforms, and services for Adobe Express, covering the entire ML lifecycle.
About the Team
The AI Foundation Team at Adobe Express aims to develop a groundbreaking AI stack using internal and external technologies to improve feature speed and quality. Develop ML models and services, collaborate with teams, improve user experience at Adobe Express.
What You'll Do
Research, design, and implement advanced ML models and pipelines for training and inference at scale, including techniques in computer vision, NLP, deep learning, and generative AI.
Integrate Large Language Models (LLMs) and agent-based frameworks to support multimodal creative workflows, enabling rich, context-aware content generation and dynamic user experiences.
Collaborate with multi-functional teams to translate product requirements into ML solutions, iterating from proof-of-concept to fully productionized services.
Develop robust platforms for continuous model training, experimentation, A/B testing, and monitoring, ensuring that model quality and relevance remain consistently high.
Leverage distributed computing technologies and cloud infrastructures to handle large-scale data processing, feature engineering, and real-time inference, optimizing for performance and cost-efficiency.
Implement reliable APIs and microservices that serve ML models to end users, ensuring alignment to standard methodologies in security, compliance, scalability, and maintainability.
Stay ahead of emerging ML research, tools, and frameworks, evaluating and integrating new technologies such as sophisticated LLMs, reinforcement learning-based agents, and innovative inference optimization techniques.
In the near future, we will expand the model coverage to include more creative tasks. We will also improve the model architectures to achieve better latency and accuracy. Additionally, we will integrate federated learning or domain adaptation strategies to reach diverse audiences.
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