2026 Intern – Machine Learning Engineer

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Ready to launch your engineering career in tech?

When you join us as an engineering intern, you’ll dive into real projects that impact the future of our products. You’ll work side-by-side with experienced teams, contribute meaningful code, and see how a global tech company builds and scales innovation.  

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Internship Details

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Location: Hamburg

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Duration: 6 months

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Start date: 1st March 2026

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End date: 31st August 2026

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Eligibility:

Students that are enrolled in Bachelor or Masters program, must be graduating the following year. Final year of study based in Hamburg.  

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Hybrid:

‍3 days per week in the office, 2 days per week work from home

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About the role

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In the Digital Video & Audio Machine Learning Team we build, train, maintain and deploy state-of-the-art machine learning technologies to our video and audio products. Adobe Sensei Features like Scene Edit Detection, Auto Reframe, Media Intelligence or Text Based Editing originated in this group.

With an increased focus on AI & ML throughout our apps, we are looking to grow and enhance our machine learning framework to cover an even wider array of use cases.

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What you will do

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• Work closely with world leading experts in the field of Machine Learning and Video Editing
• Directly work in the core processing, render and ML code of our video and audio applications.
• Enhance your skills to remain at the forefront of the newest development, testing, and deployment techniques

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What you need to succeed

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• Completing university course in computer science, or equivalent work experience
• Strong C++ coding skills, including an understanding of optimization, performance ramifications of coding decisions, and object-oriented design.
• Strong Python coding skills for evaluation and writing proof of concept code.
• Experience in building, validating and evaluating machine learning models is a plus.
• Experience in working with different device ML pipeline technologies (CoreML, ONNX, etc) is a plus.

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What to expect from the recruitment process. Our selection process typically consists of three stages as follows:  

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60-minute Online Assessment.  

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90-minute Technical Interview with the team.  

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45-minute Soft-Skills Interview with the Hiring Manager.

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