Principal Scientist, Foundation Model Understanding Data Architect

About the Role We are seeking a Principal Scientist (P60) to define and lead the data and semantic architecture that enables Adobe Firefly’s next‑generation unified foundation models—models that natively combine understanding, reasoning, and generation within a single system. This role sits within the Applied Science and Machine Learning (ASML) organization and operates at the highest level of technical leadership. You will shape how meaning, intent, and abstraction are represented and learned at foundation‑model scale, influencing multiple generations of models and products. This is a highly strategic individual contributor role with broad organizational impact. What You’ll Do Foundation Model Data Vision Define the multi‑year vision for understanding‑centric data that enables unified comprehension and generation. Establish core principles for semantic representation, supervision, and curriculum at foundation‑model scale. Identify limitations in existing data paradigms and drive the invention of new approaches. Semantic Architecture & Alignment Design canonical semantic abstractions that bridge perception‑level signals with high‑level concepts such as intent, reasoning, and compositional structure. Lead the evolution of supervision schemas toward rich, model‑interpretable semantic signals. Guide the use of multimodal and vision‑language models to bootstrap scalable understanding data. Data Curriculum & Model Behavior Define understanding‑focused data curricula across model scale and training phases. Lead ablations to quantify how semantic data choices affect generalization, controllability, and robustness. Balance organic, synthetic, and model‑generated data to optimize learning efficiency. Organizational Leadership Serve as the technical authority for foundation‑model understanding data across Adobe. Influence research, infrastructure, and product roadmaps through principled, data‑driven guidance. Mentor senior scientists and architects; set standards for rigor and reproducibility. What You Need to Succeed 10+ years of experience in ML, data systems, or AI research, including leadership on large‑scale or foundation models. Demonstrated impact shaping data, learning paradigms, or representations for LLMs or multimodal models. Deep expertise in semantic representation, reasoning, and abstraction. Strong intuition for interactions between data, model architecture, and training dynamics. Ability to influence senior technical and business leaders through clear technical judgment. Education Ph.D. in Computer Science, Machine Learning, AI, or a related field strongly preferred. About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity. Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours. Let’s Adobe together At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture, focus on people, purpose and community, Adobe for All, comprehensive benefits programs, the stories we tell, the customers we serve, and how you can help us advance our mission of empowering everyone to create. Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religi ... (truncated, view full listing at source)