Job ID: 2991704 | Amazon Development Centre (London)
Limited 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. 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), Retrieval-Augmented
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 Amazon-scale 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 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 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
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 your models into production,
working closely with software engineers. - Establish automated
processes for large-scale data analysis and generation,
machine-learning model development, model validation and serving. -
Communicate results and insights to both technical and
non-technical 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
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. BASIC QUALIFICATIONS - Experience with
machine learning/statistical modeling data analysis tools and
techniques, and parameters that affect their performance -
Experience applying theoretical models in an applied environment -
Experience working as a Data Scientist - Experience with data
scripting languages (e.g. SQL, Python, R etc.) or
statistical/mathematical software (e.g. R, SAS, or Matlab)
PREFERRED QUALIFICATIONS - Experience in Python, Perl, or another
scripting language - Experience in a ML or data scientist role with
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https://amazon.jobs/content/en/how-we-hire/accommodationsfor more
information. If the country/region you’re applying in isn’t listed,
please contact your Recruiting Partner. Posted: May 22, 2025
(Updated 2 days ago) Posted: May 20, 2025 (Updated 5 days ago)
Posted: February 26, 2025 (Updated 15 days ago) Posted: April 2,
2025 (Updated 19 days ago) Amazon is an equal opportunity employer
and does not discriminate on the basis of protected veteran status,
disability, or other legally protected status.
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