2025 Applied Scientist Internship, Amazon University Talent Acquisition Are you a MS or PhD student interested in a 2025 Internship in the field of machine learning, deep learning, speech, computer vision, automated reasoning, optimization, or predictive modelling?
If so, we want to hear from you!
We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems.
Key job responsibilities:
Own the design and development of end-to-end systems. Write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. Work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. Design new algorithms, models, or other technical solutions whilst experiencing Amazon's customer focused culture. Collaborate with diverse groups of people and cross-functional teams to solve complex business problems. BASIC QUALIFICATIONS Experience programming in Java, C++, Python or related language. Enrolled in a PhD or Master's degree in Computer Science, Machine Learning, Engineering, Operations Research, Statistics or related fields. PREFERRED QUALIFICATIONS Have publications at top-tier peer-reviewed conferences or journals. Experience in designing experiments and statistical analysis of results. Experience implementing algorithms using toolkits and self-developed code. Experience in solving business problems through machine learning, data mining and statistical algorithms. Amazon is an equal opportunities employer, and we value your passion to discover, invent, simplify and build.
We welcome applications from all members of society irrespective of age, sex, disability, sexual orientation, race, religion or belief.
Amazon is committed to a diverse and inclusive workplace.
Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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