The Amazon AI Research Scientist Internship 2026 offers students and researchers an opportunity to gain practical experience in artificial intelligence research and develop solutions for real-world applications.
The global artificial intelligence market was valued at nearly USD 260 billion in 2025 and is projected to exceed USD 1.2 trillion by 2030, highlighting the growing demand for advanced AI research and technical expertise across industries.
The internship may be suitable for Master’s and PhD students pursuing degrees in computer science, artificial intelligence, machine learning, statistics, mathematics, or related technical fields.
During the internship, Amazon AI Research Scientist Interns may collaborate with scientists, engineers, and research teams while contributing to AI research projects and gaining exposure to large-scale AI systems and technologies.
About Amazon AI Research Scientist Internship
Amazon is a global technology and e-commerce company founded in 1994 by Jeff Bezos.
Headquartered in Seattle, Washington, Amazon operates across areas including e-commerce, cloud computing, artificial intelligence, digital streaming, consumer devices, and logistics.
Amazon has a significant presence in India, with corporate offices and technology teams in cities including Bengaluru, Hyderabad, Chennai, Delhi, Pune, and Mumbai.
Amazon’s Hyderabad campus is its largest corporate building globally, while its Bengaluru operations include a 1.1-million-square-foot campus supporting more than 7,000 employees.
Amazon also offers internship programmes that provide students and researchers with opportunities to gain practical industry experience, develop technical skills, and contribute to research and real-world projects across its technology teams.
Related : AI Research Scientist Internship
Eligibility
Candidates applying for the Amazon AI Research Scientist Internship 2026 may need to meet the following requirements:
- Pursuing a Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, or a related technical field
- Strong academic performance and research fundamentals
- Knowledge of machine learning, deep learning, and artificial intelligence concepts
- Proficiency in Python, C++, Java, or similar programming languages
- Understanding of algorithms, data structures, statistics, probability, and mathematical concepts
- Experience with machine learning frameworks such as PyTorch, TensorFlow, or related tools
- Research experience in areas such as NLP, computer vision, generative AI, reinforcement learning, or related fields
- Strong analytical, problem-solving, research, and communication skills
- Ability to work effectively in a collaborative research environment
Related : Google AI Research Scientist Internship
Application Process
Candidates interested in the Amazon AI Research Scientist Internship 2026 can follow these steps:
- Visit the Amazon Jobs website and search for Amazon AI Research Scientist Internship opportunities available for students and researchers.
- Review the job description carefully and check the required educational qualifications, research experience, technical skills, location, and application requirements.
- Highlight relevant AI research projects, publications, programming skills, research experience, coursework, technical skills, and GitHub repositories on your resume or CV.
- Showcase research or projects involving Natural Language Processing (NLP), Computer Vision, Generative AI, Deep Learning, Reinforcement Learning, or other relevant AI fields.
- Complete the online application and submit your resume or CV, academic information, and other requested documents.
- Depending on the role, shortlisted candidates may be asked to complete a technical assessment or research-related evaluation.
- Candidates who progress further may participate in technical and research interviews covering machine learning, algorithms, statistics, mathematical concepts, research experience, and previous projects.
Selection Process
The Amazon AI Research Scientist Internship selection process may include the following stages:
- Application Screening: Review of academic background, research experience, technical skills, publications, and projects
- Technical Assessment: Coding, problem-solving, machine learning, or technical assessments for applicable roles
- Technical Interviews: Evaluation of machine learning, algorithms, statistics, mathematics, programming, and AI concepts
- Research Discussion: Discussion of previous research, methodologies, experiments, findings, and technical contributions
- Research or Technical Presentation: Some roles may require candidates to present their research or technical work
- Behavioural Interviews: Assessment of communication, collaboration, problem-solving, and other role-related competencies
- Final Selection: Selected candidates receive an internship offer and complete the applicable onboarding process
Benefits & Perks
Amazon AI Research Scientist Interns may receive:
- Competitive internship compensation, depending on the role and location
- Opportunity to work on real-world artificial intelligence research projects
- Exposure to advanced AI and machine learning technologies
- Guidance and mentorship from research scientists and engineers
- Opportunities to develop research and technical skills
- Exposure to areas such as deep learning, NLP, computer vision, generative AI, and reinforcement learning
- Access to research tools, computing resources, and technical platforms, where applicable
- Collaboration with researchers and professionals from different technical teams
- Networking and professional development opportunities
- Potential opportunities to be considered for future research or technical roles, depending on business requirements and individual performance
FAQs
The Amazon AI Research Scientist Internship may offer compensation. The amount and structure can vary based on the internship role, location, and applicable programme.
The Amazon AI Research Scientist Internship opens based on research team requirements, locations, and hiring cycles. Candidates should regularly check Amazon's careers portal for available opportunities.
PhD students may be eligible for the Amazon AI Research Scientist Internship if they meet the educational, research, and role-specific requirements. Candidates should review the individual job description for eligibility details.
Master's students may be eligible for the Amazon AI Research Scientist Internship for roles that accept Master's candidates. Requirements vary by research team and position.
Completing the Amazon AI Research Scientist Internship does not automatically guarantee a Pre-Placement Offer (PPO). However, interns may be considered for future opportunities based on performance, business requirements, and available positions.
After submitting an Amazon AI Research Scientist Internship application, Amazon may review the candidate's academic background, research experience, and technical skills. Shortlisted candidates may then be invited to assessments and interview rounds.
Candidates can generally apply for other or future Amazon AI Research Scientist Internship opportunities if they meet the requirements of the relevant positions.
Students pursuing Master's or PhD degrees in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, or related fields may be eligible for the Amazon AI Research Scientist Internship. Requirements vary by position.
Candidates should start monitoring Amazon AI Research Scientist Internship 2026 openings several months before their preferred internship period. Research-focused positions may have specific hiring timelines, so candidates should apply as early as possible when suitable openings are available.
There is no single deadline for all Amazon AI Research Scientist Internship 2026 positions. Application deadlines can vary by research team, role, location, and hiring cycle.
Amazon does not necessarily specify a universal minimum GPA for the Amazon AI Research Scientist Internship. Academic performance, research experience, technical skills, publications, and the requirements of the individual position may be considered during the selection process.
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