Principal Scientist, Generation Data Architect (Image & Video & Audio)

Adobe
San Jose, California, United States of America / Seattle, Washington, United States of America2026-04-20Full time

About the job

Exciting opportunity for a Principal Scientist to shape the data strategy for Adobe Firefly’s multimodal foundation models. Lead research and engineering to drive innovation in image, video, and audio generation, collaborating with cross-functional teams to deliver high-quality generative models impacting millions of users. Join us to influence the future of creative technology.

Responsibilities

Develop a long-term approach to generation-focused data that improves image, video, and audio synthesis at scale; Guide decisions around data quality, diversity, and composition for foundation model training; Explore new methods to address gaps in current data approaches and improve model performance; Work closely with model teams to align data design with model architecture and training behavior; Build and refine data curricula across training stages (what data is used, when, and at what scale); Run and interpret experiments to understand how data impacts quality, motion, robustness, and efficiency; Combine organic, synthetic, and model-generated data to improve learning outcomes; Partner with research, engineering, and product teams to guide data-related decisions; Share insights that shape roadmaps across modeling, infrastructure, and applied research; Support and mentor other scientists, contributing to a culture of strong experimentation and learning; Help translate research ideas into scalable systems used in production models

Qualifications

Minimum

10+ years of experience in ML, data systems, or AI research, including work on large-scale or foundation models; Experience shaping data strategies, representations, or training approaches for generative or multimodal systems; Expertise in image and/or video and audio generation, with a strong understanding of how data affects model behavior; Understanding of how data, model architecture, and training dynamics interact; Ability to communicate complex ideas clearly and work effectively with technical and cross-functional partners

Preferred

Master’s degree or Ph.D. in Computer Science, Machine Learning, or a related field preferred