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2024 Intern - Machine Learning Engineer
2024 Intern - Machine Learning Engineer-March 2024
Seattle
Mar 29, 2026
ABOUT ADOBE
At Adobe, we’re changing the world through digital experiences by helping customers create, deliver, and optimize content.
10,000+ employees
Technology
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About 2024 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 2024 Adobe interns will be 'co-located hybrid. This means that interns will be assigned to an Adobe office location, but in-office schedules will be flexible and determined by team. All interns must live in the same state, country, and within commuting distance of their assigned Adobe office so they can be on-site as needed.

  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

  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 positionis $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 anEqual Employment Opportunityand 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 protected] 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.

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