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Amazon is looking for talented Postdoctoral Scientists to join our Amazon AGI (Artificial General Intelligence) in Fulfillment team for a one-year, full-time research position. Postdoctoral Scientists will innovate on the fundamental science of AGI, including working on combining LLMs with more classical AI task planning and AI reasoning. You will work with a team of scientists and engineers to achieve this. You will publish your results in two papers at leading venues in AI. You will be part of a larger team and have the opportunity to work on problems such as: using LLMs to generate robot task plans, using AI reasoning to verify whether a plan is correct, learning state space models and learning efficient reasoning strategies. You will have access to our latest LLMs and the opportunity to work on problems that can be applied to robotics, automation and fulfillment.Key job responsibilities
In this role you will:• Publish your innovation in top-tier academic venues and hone your presentation skills.
• Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise.A day in the life
You'll meet with your science advisor on your ideas for the project, get guidance and feedback, work together on architectures and algorithms to achieve your goals, author papers, and understand better how science works at Amazon. You'll work closely with other scientists to review your plans and results. You'll meet with engineers to implement the architecture, carry out training and inference.
• PhD in a relevant field, ideally received within 2 years of starting the program
• Publication record in either LLMs, LLMs for reasoning, classical AI Reasoning, AI Planning, AI theorem proving, AI proof planning, or other related technical fields
• Experience in machine learning practice and experience of experimental analysis
• Proficiency in other relevant technologies
• Ability to independently deliver results in a fast-paced environment
• Publications at top-tier, peer-reviewed conferences and/or journals
• Exceptional verbal and written communication skills
• Expert knowledge in the scientific domain
• Practical skills in relevant software frameworks (e.g. Python, PyTorch/TensorFlow, LLM training, AI reasoning)
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