Member of Technical Staff Intern (2026), Artificial General Intelligence (AGI)

Amazon
San Francisco2025-11-06ONSITE

About the job

Amazon has launched a new research lab in San Francisco to develop foundational capabilities for useful AI agents. We’re enabling practical AI to make our customers more productive, empowered, and fulfilled. In particular, our work combines large language models (LLMs) with reinforcement learning (RL) to solve reasoning, planning, and world modeling in both virtual and physical environments. Our research builds on that of Amazon’s broader AGI organization, which recently introduced Amazon Nova, a new generation of state-of-the-art foundation models (FMs).

Responsibilities

Design, maintain, and enhance tools and workflows that support cutting-edge research

Adapt quickly to evolving research priorities and team needs

Stay informed on the latest advancements in large language models and related research

Collaborate closely with researchers to develop new techniques and tools around emerging agent capabilities

Drive project execution, including scoping, prioritization, timeline management, and stakeholder communication

Thrive in a fast-paced, iterative environment, delivering high-quality software on tight schedules

Apply strong software engineering fundamentals to produce clean, reliable, and maintainable code

Qualifications

Minimum

Are 18 years of age or older

Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design

Are enrolled in a Bachelor's degree or above in Computer Science, Computer Engineering, Data Science, Electrical Engineering, or related STEM fields, with an expected graduation date after October 2026

Preferred

Hands-on experience in academic labs, industry internships, and/or open source development

Demonstrated ability to own an ambiguous project end-to-end, i.e., writing code, designing experiments, and interpreting results

Capacity to work autonomously and with a small team to drive research progress