
AI/ML engineering
Data Scientist, Edge AI Product Science
- Pay
- Not stated in the ad
- Location
- Cambridge
- First listed
- 28 Oct 2026
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Does this role offer visa sponsorship?
Amazon is on the UK sponsor register
The ad doesn't say either way
The ad doesn't state pay
The ad doesn't mention relocation help
Amazon has an open Data Scientist, Edge AI Product Science role in Cambridge. Amazon UK Services Ltd is on the UK Home Office register of licensed sponsors with an A rating (checked 12 Nov 2026), so it can sponsor workers. The posting doesn't state pay and doesn't mention visa sponsorship. First listed here on 28 Oct 2026.
Read from the ad by AI and can be wrong. The full ad is below.
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Data Scientist, Edge AI Product Science
Amazon Devices is an inventive research and development company that designs and engineers high-profile devices like Echo, Fire Tablets, Fire TV, and other consumer devices. We are looking for an exceptional data scientist to join our Edge AI Product Science team to advance the state-of-the-art in developing efficient multimodal deep learning models across our product portfolio. Through close hardware-software integration, we design and train models for resource efficiency across the hardware and software tech stack.
Edge AI Product Science team is looking for a talented Data Scientist who will introduce and model best practices around our dataset curation, annotation pipelines, and data driven model development. This role will take a data-first approach to improving model and system performance and work alongside other scientists to develop new evaluation methods for multimodal language models and agents for our devices, including audio and vision experiences.
Key job responsibilities
- Collaborate with cross-functional engineers and scientists to advance the state of the art in multimodal model evaluations for devices, including audio, images, and videos
- Invent and validate reliability for novel automated evaluation methods for perception tasks, such as fine-tuned LLM-as-judge
- Develop and extend our evaluation frameworks to support expanding capabilities for multimodal language models
- Analyse large offline and online datasets using Python or similar to understand model gaps, develop methods to interpret model failures, and collaborate with training teams to enhance model capabilities for product use cases
- Work closely with other scientists, compiler engineers, data collection, and product teams to advance evaluation methods
A day in the life As a Data Scientist with the Edge AI Product Science team, you'll contribute to innovative methods for evaluating new product experiences and discover ways to use data to enhance our model capabilities and enrich our customer experiences. You'll have opportunities to collaborate across teams of engineers and scientists to bring algorithms and models from inception through prototype all the way to production.
About the team Our Edge AI Product Science team brings together our unique skills and experiences to deliver state-of-the-art multimodal AI models that enable new experiences on Amazon devices. We strive to deliver customer experiences driven by AI at the edge which are only possible with tight model, hardware, and system co-design.
Basic qualifications
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- 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 with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
Preferred qualifications
- Experience in a ML or data scientist role with a large technology company
- Experience in manipulating/transforming data, model selection, model training, cross-validation and deployment at scale
- Experience with Machine Learning and Large Language Model (LLM) fundamentals, including architecture, training/inference lifecycles, and training recipe refinement
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 (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
As published on Amazon's job board, read 3 Nov 2026. The ad on their site is the one that counts.
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