Applied Science Intern
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Job Description
About the Company: Amazon Development Center (Tel Aviv) – D47
Job Description:
This internship opportunity is for MS or PhD students interested in machine learning, deep learning, speech, robotics, computer vision, optimization, quantum computing, automated reasoning, or formal methods. The role involves inventing, designing, and implementing state-of-the-art solutions for complex problems.
Key Responsibilities:
• Own the design and development of end-to-end systems.
• Write technical white papers and create roadmaps.
• Drive production-level projects supporting Amazon Science.
• Collaborate with Amazon scientists and other interns.
• Develop and deploy solutions into production.
• Design new algorithms, models, and technical solutions.
• Work with diverse teams to solve complex business problems.
A Day in the Life: The internship focuses on developing new skills, achieving personal growth, and contributing to impactful work.
Benefits:
• Competitive stipend/salary
• Experienced manager and mentor(s)
• Invitations to intern program initiatives and site events
• Networking opportunities with Amazon Scientists
• Potential to publish work at top-tier conferences
Team: Applicants are assigned to teams based on their research interests and experience.
Start Dates and Duration: Start dates vary throughout the year, with internships lasting 3-6 months (full-time) or up to 12 months (part-time). These are not remote internships. Locations are across multiple EMEA regions (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Luxembourg, Netherlands, Poland, Romania, Spain, UAE, and UK).
Basic Qualifications:
• Enrolled in a PhD or Master’s degree in Computer Science, Machine Learning, Engineering, Operations Research, Statistics, or related fields.
• Experience programming in Java, C++, Python, or a related language.
Preferred Qualifications:
• Publications at top-tier peer-reviewed conferences or journals.
• Experience designing experiments and statistically analyzing results.
• Experience implementing algorithms using toolkits and self-developed code.
• Experience solving business problems through machine learning, data mining, and statistical algorithms.
