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

Amazon Amazon · Big Tech · San Francisco, CA · Software Development

Research intern role focused on developing foundational capabilities for AI agents, combining LLMs with RL for reasoning, planning, and world modeling. The role involves running experiments, building tools to accelerate research workflows, and scaling AI systems within a fast-paced, iterative research lab environment.

What you'd actually do

  1. Design, maintain, and enhance tools and workflows that support cutting-edge research
  2. Adapt quickly to evolving research priorities and team needs
  3. Stay informed on the latest advancements in large language models and related research
  4. Collaborate closely with researchers to develop new techniques and tools around emerging agent capabilities
  5. Drive project execution, including scoping, prioritization, timeline management, and stakeholder communication

Skills

Required

  • 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

Nice to have

  • 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

What the JD emphasized

  • foundational capabilities for useful AI agents
  • combines large language models (LLMs) with reinforcement learning (RL)
  • solve reasoning, planning, and world modeling
  • agents can redefine what AI makes possible
  • build it from the ground up

Other signals

  • foundational capabilities for useful AI agents
  • combines large language models (LLMs) with reinforcement learning (RL)
  • solve reasoning, planning, and world modeling
  • agents can redefine what AI makes possible