Applied Scientist, Rufus Experiences Science

We are looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology powering Rufus, our AI-driven search and shopping assistant, helping customers with their shopping tasks at every step of their shopping journey.

This innovative role focuses on developing conversation-based, multimodal shopping experiences, utilizing multimodal large language models (MLLMs), generative AI, advanced machine learning (ML) technologies and computer vision.

Our mission in conversational shopping is to make it easy for customers to find and discover the best products to meet their needs by helping with their product research, providing comparisons and recommendations, answering product questions, enabling shopping directly from images or videos, providing visual inspiration, and more.

Key Responsibilities

• Perform hands-on analysis and modelling of enormous multimodal datasets to develop insights into how to best help customers throughout their shopping journeys
• Use deep learning, ML and MLLM techniques to create scalable language model centric solutions for building shopping assistant systems
• Innovate new methods for understanding, extracting, retrieving and summarising contextual information
• Drive end-to-end MLLM projects that have a high degree of ambiguity, scale and complexity
• Build models, perform offline and A/B test experiments, optimize and deploy models into production
• Establish automated processes for large-scale data analysis and generation
• Communicate results and insights to both technical and non-technical audiences

Basic Qualifications

• PhD, or a Master's degree and experience in CS, CE, ML or related field
• Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization
• Experience programming in Java, C++, Python or related language
• Experience in algorithms, data structures, parsing, numerical optimization, data mining, parallel computing
• Experience in building machine learning models for business application

Preferred Qualifications

• Experience with generative deep learning models like CNNs, GANs, VAEs and NF
• Experience with popular deep learning frameworks such as MxNet and TensorFlow
• Experience developing and implementing deep learning algorithms, particularly computer vision
• Publications at top-tier peer-reviewed conferences or journals
• Experience leveraging computer vision libraries to deliver new solutions
• Experience deploying solutions to AWS or other cloud platforms
• Excellent communication skills and strong desire to write production-quality code

About the Team

You will be part of a dynamic science team based in London, working alongside over 100 engineers, designers and product managers, focused on shaping the future of AI-driven shopping experiences at Amazon. This team works on every aspect of the shopping experience, from understanding multimodal user queries to planning and generating answers that combine text, image, audio and video.