Amazon is looking for talented Postdoctoral Scientists to join our team for a one-year, full-time research position. Postdoctoral Scientists will innovate in key areas of machine learning, natural language processing, computer vision, automated reasoning, robotics, or quantum technologies.
As part of the Rufus Features Science team in London, the postdoc will work on shaping the future of AI-driven shopping experiences at Amazon. In particular, the project focuses on conversational search in shopping, developing next-generation conversational search systems in the shopping domain that seamlessly bridge natural shopping dialogues with precise product retrieval and recommendation. Key challenges include developing new methods for grounding conversational context in product attribute space, designing efficient retrieval mechanisms that can handle both structured product metadata and unstructured conversational context, and creating evaluation frameworks that capture both conversation quality and search relevance. The project will extend beyond traditional conversational search paradigms by integrating agentic frameworks that can proactively identify, clarify, and refine user needs through strategic dialogue management, while simultaneously orchestrating multiple specialized retrieval agents for different aspects of the shopping journey (e.g., attribute extraction, price comparison, review analysis, and specification matching).
We experiment and innovate relentlessly. Science is core in our offering to shoppers, advertisers and customers. Our scientists apply machine learning, optimization, causal modeling and game theory at scale to enhance the customer experience, help advertisers reach relevant audiences, and support brand building. We are seeking talented scientists to invent cutting-edge techniques in a variety of areas and innovate on behalf of shoppers, advertisers, and customers.
In this role you will:
Lead research projects in conversational search and retrieval-augmented systems
Develop novel architectures combining dialogue management with product search
Design and implement evaluation frameworks for agentic conversational shopping systems
Publish research findings in top-tier conferences and journals
Mentor junior researchers and contribute to the team's scientific direction PhD in Computer Science, Machine Learning, Information Retrieval or related field
Strong publication record in NLP, Information Retrieval, or Conversational AI
Experience with large language models and retrieval-augmented generation
Research background in conversational systems or dialogue management
Experience with modern deep learning frameworks (PyTorch, TensorFlow)
Excellent written and verbal communication skills Knowledge of multi-agent systems and tool-use frameworks
Experience with e-commerce or shopping domain applications
Publications at top venues (ACL, NeurIPS, SIGIR, AAAI, etc.)
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