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Member of Technical Staff - Machine Learning Engineer, AGI Autonomy Job ID: 2916912 | Services LLC 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). Our lab is a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We're entering an exciting new era where agents can redefine what AI makes possible. We'd love for you to join our lab and build it from the ground up! Key Job Responsibilities You will contribute directly to AI agent development in a research engineering role: running experiments, building tools to accelerate scientific workflows, and scaling up AI systems. You will be hired as a Member of Technical Staff. BASIC QUALIFICATIONS 3+ years of industry experience on a machine learning team Proficiency in Python, Java, C++, or related language Experience with deep learning methods and tools, e.g., PyTorch, JAX PREFERRED QUALIFICATIONS Experience building and optimizing production-grade AI systems, e.g., for self-driving, simulation, or LLM applications Willingness to step outside typical role boundaries to get things done - every member of technical staff is expected to write code, design experiments, and interpret results Capacity to work autonomously and with a small team to drive research progress Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. #J-18808-Ljbffr