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Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.
We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!
Documents have been integral part of our day-to-day business for centuries. Today’s enterprises leverage documents to drive all essential and business critical processes and functions. Adobe PDF was, and to a large extent, still is the primary digital format for reliably sharing and distributing documents. During the last two decades of PDF’s dominance, the world around us has changed dramatically. World Wide Web, the mobile devices and advancements in AI have transformed the lives of all. In this new era of AI-powered digital business, the challenge we have is to invent, design and productize that document of the future and redefine the user experiences around the document.
As a research scientist in Document Intelligence Lab (DIL), you will provide technical leadership in research, architect and develop machine learning solutions at scale regards document structure, semantics understanding, knowledge extraction and auto-generation cross modalities (e.g. image, language and layout structure). You will leverage Adobe’s unique data sources and customer relationships which include not only content (such as images, videos, texts, voicees), but also how the customers interacting with those contents (such as authoring, sharing, viewing, retrieving, and collaborating) in the context of diverse verticals (e.g. financial services, healthcare, government and etc.).
In addition, you will do:
- Demonstrate technical proficiency in natural language understanding, generation, knowledge extraction & construction and machine learning methods that deal with multi-modality data (e.g. text, image, graph, etc.)
- Initiate, lead and execute research initiatives by collaborating with researchers and engineers in cross-disciplinary and cross-functional environment
- Keep abreast of the latest developments in the fields by continuous learning and proactively champion new ideas and new problem definitions
Required Qualifications
- PhD in Computer Science, Electrical Engineering or relevant majors with research specialization in artificial intelligence, machine learning, natural language processing and understanding, multi-modal document analysis.
- Proficient in one or more programming languages such as Python, R, Java, Scala and C/C++
- Familiar with one or more state-of-art deep learning frameworks, such as Tensorflow, PyTorch, Keras, Caffe, Torch.
- Strong analytical and quantitative problem-solving ability.
- Demonstrated track record of innovation and creativity in the machine learning domains, especially in NLP or computer vision.
- Excellent communication, relationship skills and a strong team player.
Preferred Qualifications
- Experience of architecting and applying state-of-art deep learning techniques to NLP and computer vision applications.
- Experience of working with very large data sets with multi-modal elements (image, text. Etc.).
- Strong publication records in relevant areas
At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).
In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.
Adobe is proud to be an Equal Employment Opportunity and affirmative action employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more.
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