Manager, Applied Science
Adobe · San Jose, CA · Engineering and Product
About this role
Adobe is hiring a manager-level Engineering Manager in the software engineering function based in San Jose, CA. The posting calls out experience with Express, LLMs, Distributed Systems, System Design and roughly 2+ years of relevant work. Listed education preference: a master's degree or equivalent. Compensation is listed at $149,300–$324,450 per year.
- Role
- Engineering Manager
- Function
- software engineering
- Level
- manager
- Track
- hybrid
- Employment
- Full-time
- Location
- San Jose, CA
- Experience
- 2+ years
- Education
- Master's degree
- Department
- Engineering and Product
- Posted
- Mar 16, 2026
More roles at Adobe
Job description
from Adobe careersThe Opportunity
Adobe Firefly Applied Science & Machine Learning (ASML) is looking for a Manager, Applied Science – Generative AI Foundations to lead a team building core systems that support training and development of foundation models for generative AI, spanning image, video, and multimodal generation.
This role is designed for a technical lead manager who combines strong software engineering and systems experience with applied ML understanding and people leadership. You will lead a team responsible for foundational training frameworks, tooling, and codebases that enable large-scale experimentation, reliable execution, and rapid iteration across multiple generative AI efforts at Adobe.
The focus of this role is on foundational capabilities and engineering systems that support many models and teams, rather than ownership of a single model or research area. You will work closely with applied researchers, ML engineers, and product partners to turn evolving research and product needs into scalable, maintainable, and production-ready systems.
Success in this role requires strong engineering judgment, comfort with ambiguity, and the ability to guide both system design and applied ML workflows, while scaling impact through effective team leadership and execution.
What You’ll Do
- Lead and grow a team of applied scientists and engineers working on core generative AI training systems