Our Company
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!
The Opportunity
The Photoshop ICE Research Lab is seeking summer interns! As a contributor behind Generative Fill and the driving force behind distractor removal technologies at Adobe, the ICE Lab plays a pivotal role in advancing creative tools.
During this internship, you’ll have the opportunity to apply AI and machine learning techniques to real-world customer data, contributing to research projects that power innovative features in Photoshop and Lightroom that impact millions of users worldwide. You may also collaborate with our research team to refine and improve new technologies, pushing the boundaries of what’s possible in digital imaging.
All 2025 Adobe interns will be co-located hybrid. This means that interns will work between their assigned office and home. 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.
What You’ll Do
- Apply data mining, machine learning, and NLP to real-world problems and datasets
- Analyze massive data sets using statistical techniques to generate insights and make predictions
- Develop machine learning models at scale from conceptualization to business impact
- Extract and analyze data to understand the customer product life cycle and value realization from the product
What You Need To Succeed
- Currently enrolled full time and pursuing a Masters or PhD degree in Computer Science, Data Science, Information Science, Statistics, Applied Mathematics, or Engineering is desired; with an expected graduation date of December 2025 – June 2026
- Publication Record: Strong track record of publishing in top-tier machine learning and data science venues (e.g., NeurIPS, ICML, ICLR, AAAI, KDD, JMLR) or other leading journals and conferences in related fields. Demonstrated ability to contribute to impactful, cutting-edge research.
- Solid understanding of SQL and Python
- Solid understanding of machine learning/data mining/statistical modeling concepts, and a track record solving problems with these methods
- Ability to apply machine learning/statistical techniques such as supervised/unsupervised learning, NLP techniques, LLM, time series forecasting, explainable AI, reinforcement learning, A/B testing, causal etc.
Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $45.00 -- $55.00 hourly. Your recruiter can share more about the specific pay rate for your job location during the hiring process.
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.
Adobe aims to make Adobe.com accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call (408) 536-3015.
Adobe values a free and open marketplace for all employees and has policies in place to ensure that we do not enter into illegal agreements with other companies to not recruit or hire each other’s employees.
