Applied Scientist Rufus Experiences Science
Applied Scientist Rufus Experiences Science
Posted on :
06-04-2025
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1 Vacancy
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Job Description
We are looking for a passionate talented and inventive Applied Scientist with a strong machine learning background to help build industryleading language technology powering Rufus our AIdriven search and shopping assistant helping customers with their shopping tasks at every step of their shopping journey.
This innovative role focuses on developing conversationbased 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. We do this by pushing the SoTA in Natural Language Processing (NLP) Generative AI Multimodal Large Language Model (MLLM) Natural Language Understanding (NLU) Machine Learning (ML) RetrievalAugmented Generation (RAG) Computer Vision Responsible AI LLM Agents Evaluation and Model Adaptation.
Key job responsibilities
As an Applied Scientist on our team you will be responsible for the research design and development of new AI technologies that will shape the future of shopping experiences. You will play a critical role in driving the development of multimodal conversational systems in particular those based on large language models information retrieval recommender systems and knowledge graph to be tailored to customer needs. You will handle Amazonscale use cases with significant impact on our customers experiences. You will collaborate with scientists engineers and product partners locally and abroad. Your work will include inventing experimenting with and launching new features products and systems.
You will:
Perform handson 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 based on a rich set of structured and unstructured contextual signals.
Innovate new methods for understanding extracting retrieving and summarising contextual information that allows for the effective grounding of MLLMs considering memory compute latency and quality.
Drive endtoend MLLM projects that have a high degree of ambiguity scale and complexity.
Build models perform offline and A/B test experiments optimize and deploy your models into production working closely with software engineers.
Establish automated processes for largescale data analysis and generation machinelearning model development model validation and serving.
Communicate results and insights to both technical and nontechnical audiences including through presentations and written reports and publish your work at internal and external conferences.
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 AIdriven 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.
PhD or a Masters degree and experience in CS CE ML or related field
Experience in stateoftheart deep learning models architecture design and deep learning training and optimization and model pruning
Experience programming in Java C Python or related language
Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing highperformance computing
Experience in building machine learning models for business application
Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs GANs VAEs and NF
Experience with popular deep learning frameworks such as MxNet and Tensor Flow
Experience developing and implementing deep learning algorithms particularly with respect to computer vision algorithms
Have publications at toptier peerreviewed conferences or journals
Experience leveraging and augmenting a large code base of computer vision libraries to deliver new solutions.
Experience deploying solutions to AWS or other cloud platforms.
Excellent communication skills solid work ethic and a strong desire to write productionquality code.
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover invent simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice to know more about how we collect use and transfer the personal data of our candidates.
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.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
This innovative role focuses on developing conversationbased 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. We do this by pushing the SoTA in Natural Language Processing (NLP) Generative AI Multimodal Large Language Model (MLLM) Natural Language Understanding (NLU) Machine Learning (ML) RetrievalAugmented Generation (RAG) Computer Vision Responsible AI LLM Agents Evaluation and Model Adaptation.
Key job responsibilities
As an Applied Scientist on our team you will be responsible for the research design and development of new AI technologies that will shape the future of shopping experiences. You will play a critical role in driving the development of multimodal conversational systems in particular those based on large language models information retrieval recommender systems and knowledge graph to be tailored to customer needs. You will handle Amazonscale use cases with significant impact on our customers experiences. You will collaborate with scientists engineers and product partners locally and abroad. Your work will include inventing experimenting with and launching new features products and systems.
You will:
Perform handson 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 based on a rich set of structured and unstructured contextual signals.
Innovate new methods for understanding extracting retrieving and summarising contextual information that allows for the effective grounding of MLLMs considering memory compute latency and quality.
Drive endtoend MLLM projects that have a high degree of ambiguity scale and complexity.
Build models perform offline and A/B test experiments optimize and deploy your models into production working closely with software engineers.
Establish automated processes for largescale data analysis and generation machinelearning model development model validation and serving.
Communicate results and insights to both technical and nontechnical audiences including through presentations and written reports and publish your work at internal and external conferences.
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 AIdriven 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.
PhD or a Masters degree and experience in CS CE ML or related field
Experience in stateoftheart deep learning models architecture design and deep learning training and optimization and model pruning
Experience programming in Java C Python or related language
Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing highperformance computing
Experience in building machine learning models for business application
Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs GANs VAEs and NF
Experience with popular deep learning frameworks such as MxNet and Tensor Flow
Experience developing and implementing deep learning algorithms particularly with respect to computer vision algorithms
Have publications at toptier peerreviewed conferences or journals
Experience leveraging and augmenting a large code base of computer vision libraries to deliver new solutions.
Experience deploying solutions to AWS or other cloud platforms.
Excellent communication skills solid work ethic and a strong desire to write productionquality code.
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover invent simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice to know more about how we collect use and transfer the personal data of our candidates.
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.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Employment Type
Full-Time
Key Skills
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