Sr Applied Scientist, Generative AI/ML
Adobe · Seattle, WA · Engineering and Product
About this role
Adobe is hiring a senior-level Applied Scientist in the machine learning function based in Seattle, WA. The posting calls out experience with Express, PyTorch, LLMs, Computer Vision. Compensation is listed at $142,700–$270,950 per year.
- Role
- Applied Scientist
- Function
- machine learning
- Level
- senior
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Seattle, WA
- Department
- Engineering and Product
- Posted
- May 19, 2026
More roles at Adobe
Job description
from Adobe careersThe Opportunity
Adobe is seeking to add Applied Scientists in Generative AI to our world-class AI Platform team. We are specifically looking for scientists with expertise in preparing data, training, fine-tuning and adapting large foundation models across all modalities: images, video, 3D, LLMs and cross-modal setups.
We welcome outstanding candidates in all related technical fields, such as Machine Learning, Deep Learning, Computer Vision, and Natural Language Processing. The related applications include image/video/3D generation, editing, and understanding, conditioned on controls stemming from large language models, or other innovative interactions tailored for creative workflows, and multimodal priors.
What You'll Do
- Conduct pioneering research and development in Generative AI for visual (image/video/3D), audio, and multi-modal outputs.
- Develop and deploy novel generative AI technologies to existing and new Adobe Products.
- Research and develop novel large-scale foundation models with deep reasoning and world-building capabilities.
- Collaborate with world-class researchers and ML engineers to bring research ideas to creative workflows used by millions.
- Publish and present your work in world-class scientific venues in CV/AI/ML/CG fields
Required Qualifications
- Ph.D. in Computer Science, CV/AI/ML/CG or related fields and 1+ years professional experience.
- Research or industry experience in training Generative AI models (pre-training and/or post-training) in at least one of the following modalities: image, video, 3D, or audio.