2025 Intern - Machine Learning Engineer

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  

Adobe is looking for a Machine Learning intern who will apply AI and machine learning techniques to big-data problems to help Adobe better understand, lead and optimize the experience of its customers. 

By using predictive models, experimental design methods, and optimization techniques, the candidate will be working on the research and development of exciting projects like real-time online media optimization, sales operation analytics, customer churn scoring and management, customer understanding, product recommendation and customer lifetime value prediction.  

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  

• Develop predictive models on large-scale datasets to address various business problems with statistical modeling, machine learning, and analytics techniques. 
• Develop and implement scalable, efficient, and interpretable modeling algorithms that can work with large-scale data in production systems 
• Collaborate with product management and engineering groups to develop new products and features. 

What You Need to Succeed  

• Currently enrolled full time and pursuing a Master’s or PhD degree in Computer Science, Computer Engineering; or equivalent experience required with an expected graduation date of December 2025 – June 2026 
• Good understanding of statistical modeling, machine learning, deep learning, or data analytics concepts. 
• Proficient in one or more programming languages such as Python, Java and C 
• Familiar with one or more machine learning or statistical modeling tools such as R, Matlab and scikit learn 
• Strong analytical and quantitative problem-solving ability. 
• Excellent communication, relationship skills and a team player 
• Ability to participate in a full-time internship between May-September 

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 will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.

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.