Location
London, with opportunities across multiple locations in the EMEA region including Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, Spain, South Africa, and UAE. Please note these are not remote internships.

Hours
Full-time internship, duration varies from 3 to 6 months with flexible start dates throughout the year.

Salary
Competitive stipend/salary offered for all internships.

About the Role
Are you a MS or PhD student interested in an internship in 2026 focused on machine learning, deep learning, generative AI, large language models, speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods? This internship offers the opportunity to invent, design, and implement state-of-the-art solutions for novel problems. As an Applied Science Intern, you will own the design and development of end-to-end systems, write technical white papers, create roadmaps, and drive production-level projects supporting Amazon Science. You will collaborate closely with Amazon scientists and other interns to develop and deploy solutions into production. The role involves designing new algorithms, models, or technical solutions while embracing Amazon's customer-focused culture. You will work with diverse groups and cross-functional teams to solve complex business challenges. Interns also benefit from mentorship, professional networking, and the potential to publish work at top-tier conferences. Join us to grow your skills and make an impact that changes the world.

Experience
- Programming experience in Java, C++, Python, or related languages.
- Enrolled in a PhD or Master's degree program in Computer Science, Machine Learning, Engineering, Operations Research, Statistics, or related fields.

About you
- Ability to work effectively with diverse groups and cross-functional teams.
- Passionate about solving complex business problems through innovative scientific approaches.
- Motivated to grow professionally and contribute to cutting-edge research and development.

Qualifications
- Preferred: Publications at top-tier peer-reviewed conferences or journals.
- Experience designing experiments and performing statistical analysis.
- Experience implementing algorithms using toolkits and custom code.
- Experience applying machine learning, data mining, and statistical algorithms to solve business problems.