Data Scientist, Edge AI Product Science

Amazon Inc.; Cambridge; On-site; GBP 65,000 - 95,000; Full time

Job summary

Amazon's Edge AI Product Science team in Cambridge is seeking a Data Scientist to advance multimodal model evaluation for devices, including audio, vision, and language components. You will work with cross-functional engineers to build robust assessment methods.

You will curate datasets, develop annotation pipelines, and prototype evaluation strategies that guide model improvement and deployment at the edge.

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).

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

Skills

Statistical analysis

ML modeling

Data visualization

Education

Master's degree in a quantitative field

Tools

Python

SQL

R

Matlab

SAS

Job description

Job ID: 10590206 | Evi Technologies Limited

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 your 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.

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Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Veterans, military spouses, and people with disabilities are encouraged to apply.