Research Intern 2027 (San Jose) - Applied & Research Scientist

The Opportunity

Adobe Researchers and Applied Scientists are building the next generation of advanced technologies and user experiences, creating new forms of creativity, freeing people from routine tasks, and helping enterprises understand and act quickly on customer and business insights. Our teams publish in leading journals and conferences, partner with product teams to ship high-profile features, and explore new product opportunities across a wide range of domains. We foster collaborations that extend beyond the internship, whether that means contributing to your PhD thesis or seeing your work carried into a shipped product.

All 2027 Adobe interns will be co-located and hybrid. Interns will be based in the office where their manager and/or team are located, where they will get the most support to ensure collaboration and the best employee experience. Managers and their organization will determine the frequency they need to go into the office to meet priorities.

Adobe Research Focus Areas

• Audio
• Computer Vision and Imaging & Video
• Content Intelligence
• Document Intelligence
• Data Intelligence
• Graphics (2D & 3D)
• Systems, Models & Languages
• Intelligent Agents & Assistants
• Natural Language Processing
• Human Computer Interaction

What You'll Do

Under the direction of an Adobe mentor, you will:

• Pursue a research problem to apply to Adobe's products, with the possibility of academic publication or direct product integration
• Develop new algorithms, run experiments, and produce demonstration prototypes
• Depending on project focus, contribute to translating research into working models, pipelines, or product-facing features
• Document and present your work, both verbally and in writing

What You Need to Succeed

Minimum Qualifications

• Current PhD or master's student in computer science, or related field (exceptional undergraduates will also be considered)
• Ability to scope or formulate a research question, design an appropriate baseline and evaluation methodology, and reason about ML/statistical fundamentals
• Strong communication skills and teamwork experience
• Comfort working across the spectrum from open-ended research to applied, product-facing development, according to project specifications

Preferred Qualifications

• Relevant publications or research contributions at leading venues such as NeurIPS, ICML, ICLR, CVPR, or ACL
• Ability to balance exploratory thinking with delivering clear, practical results
• Passion for solving real-world problems with web-scale data, using and inventing innovative Machine Learning algorithms
• Demonstrates ownership, adaptability, and clear communication of your own work and its limitations