متدرب عالم علوم تطبيقية (Applied Scientist Intern) – 2026

2026 Applied Scientist Intern, Amazon University Talent Acquisition

Key Responsibilities

• Design and develop end-to-end applied science systems from concept to production.
• Create and implement novel algorithms, models, and technical solutions.
• Write technical documentation and white papers to support research and development initiatives.
• Build technical roadmaps and contribute to production-grade projects aligned with Amazon Science.
• Collaborate with applied scientists, engineers, and other science interns across cross-functional teams.
• Deploy scalable solutions that align with a customer-focused, data-driven culture

Internship Experience

• This role offers hands-on exposure to high-impact research and applied science projects.
• Interns gain experience in solving real business and technical challenges using AI-driven and data-centric approaches, while continuously developing technical and professional skills.
• The internship environment supports innovation, collaboration, and measurable impact, allowing interns to contribute to technologies that influence products used globally.

Internship Benefits

• Competitive internship salary or stipend
• Dedicated manager and scientific mentor(s)
• Access to intern programs, scientific events, and site activities
• Opportunities to build a strong professional network with Amazon Scientists
• Potential to publish research at top-tier peer-reviewed conferences or journals

Team & Program Details

• Applications are reviewed on a rolling basis
• Candidates are matched with teams based on research interests and academic background
• Start dates are available throughout the year
• Full-time internship duration ranges from 3 to 6 months

Basic Qualifications

• Programming experience in Python, Java, C++, or related languages
• Current enrollment in a Master’s or PhD program in Computer Science, Machine Learning, Engineering, Operations Research, Statistics, or a related field

Preferred Qualifications

• Publications in top-tier peer-reviewed conferences or journals
• Experience implementing algorithms using machine learning frameworks, research toolkits, or custom-developed code
• Proven ability to solve business or scientific problems using machine learning, data mining, and statistical methods