Data Scientist, Edge AI Product Science

Amazon Science; Cambridge; Presencial; GBP 70 000 - 120 000; Tempo integral

Resumo da oferta

Amazon Devices is seeking an exceptional Data Scientist to join the Edge AI Product Science team. You will advance multimodal deep learning model evaluations across our devices, driving data-first improvements to model and system performance in conjunction with hardware and software teams.

You will curate datasets and develop evaluation methods for multimodal language models and agents, including audio and vision experiences, with opportunities to deploy produced insights into product use cases.

Qualificações

• Master's degree in a quantitative field such as statistics, mathematics, data science, economics, engineering, or computer science.
• Experience with machine learning/statistical modeling and data analysis tools.
• Experience applying theoretical models in an applied environment.

Responsabilidades

• Collaborate with cross-functional engineers and scientists to advance multimodal model evaluations for devices (audio, images, video).
• Invent and validate automated evaluation methods for perception tasks including LLM-as-judge.
• Develop and extend evaluation frameworks for multimodal language models.
• Analyse large offline/online datasets using Python to understand model gaps and improve capabilities.
• Work with scientists, engineers, data collection and product teams to advance evaluation methods.

Conhecimentos

Multimodal ML

Data analysis

Python

Experiment design

Formação académica

Master's degree in quantitative field

Ferramentas

SQL

Python

R

Matlab

SAS

Descrição da oferta de emprego

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

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