2026 Applied Science Internship - United States, PhD Student Science Recruiting, Frontier AI & Robotics

Amazon is seeking an Applied Science Intern to join their elite team of researchers and engineers at the forefront of applied science in robotics. This internship offers the opportunity to work on groundbreaking research projects at the intersection of AI and robotics, collaborating with cross-functional teams to develop innovative solutions.

What you'll do:

• Develop novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of LLMs and generative AI for robotics
• Tackle challenging, groundbreaking research problems on production-scale data, with a focus on robotic perception, manipulation, and control
• Collaborate with cross-functional teams to solve complex business problems, leveraging your expertise in areas such as deep learning, reinforcement learning, computer vision, and motion planning
• Demonstrate the ability to work independently, thrive in a fast-paced, ever-changing environment, and communicate effectively with diverse stakeholders

What they're looking for:

• Are enrolled in a PhD
• Can relocate to where the internship is based
• Experience programming in Java, C++, Python or related language
• Must be available for full-time (40 hours per week) internship for the whole duration of the internship
• Strong background in machine learning, deep learning, and/or robotics
• Publication record at science conferences such as NeurIPS, CVPR, ICRA, RSS, CoRL, and ICLR
• Experience in areas such as multimodal LLMs, world models, image/video tokenization, real2Sim/Sim2real transfer, bimanual manipulation, open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, and end-to-end vision-language-action models
• Proficiency in Python, Experience with PyTorch or JAX
• Excellent problem-solving skills, attention to detail, and the ability to work collaboratively in a team
• Have publications at top-tier peer-reviewed conferences or journals
• Experience in designing experiments and statistical analysis of results

Benefits:

• Equity
• Sign-on payments
• Full range of medical, financial, and/or other benefits