Help us unlock information, weave artificial intelligence into our products, and invent the
future. The Adobe Document Cloud’s Data Team is looking for a taxonomist to help us define
the data needs for all machine learning (ML) efforts in Document Cloud. The Adobe Document
Cloud is responsible for technologies for creating, manipulating and consuming PDF files across
a range of services, mobile apps and desktop products. The flagship PDF application within the
Adobe Document Cloud is Adobe Acrobat, which is installed on over a billion devices and opens
billions of PDFs every year.
Adobe Document Cloud is pushing the boundaries of Document Intelligence by leveraging
machine learning. As the Data Team, our mandate is to support all machine learning projects
within Document Cloud by providing them with high quality labeled data. Clean data starts with
clear explanations. The taxonomist’s role is to formulate those explanations by distilling what
they learn from researchers, product management, and subject-matter experts into rules that
are both precise and easily understandable by non-experts who are hired to annotate our data.
The resulting guidelines will be used by teams of annotators as they label data for training and
evaluating machine learning models.
If you have a passion for detail and want to help build Adobe’s next revolution in how people all
over the world communicate, we’d love to hear from you!
What you’ll do
What you need to succeed
At Adobe, you will be immersed in an exceptional work environment that is recognized throughout the world on . You will also be surrounded by colleagues who are committed to helping each other grow through our unique approach where ongoing feedback flows freely.
If you’re looking to make an impact, Adobe's the place for you. Discover what our employees are saying about their career experiences on the and explore the meaningful we offer.
Adobe is an equal opportunity employer. We welcome and encourage diversity in the workplace regardless of race, gender, religion, age, sexual orientation, gender identity, disability or veteran status.