Sr. Applied Scientist, Silicon and Systems Group Edge AI

Amazon Devices; Cambridge; On-site; GBP 80,000 - 100,000; Full time

Job summary

An innovative tech firm in Cambridge is seeking a Sr. Applied Scientist to lead advancements in multimodal evaluations across devices. This role involves collaboration with cross-functional teams to develop evaluation methods, analyze datasets, and enhance model capabilities. Ideal candidates should have a PhD in a quantitative field and experience in programming and machine learning. The work environment encourages innovation and teamwork, making it an exciting opportunity for contributing to cutting-edge technologies.

Qualifications

• PhD in engineering, technology, computer science, or related field.
• Experience programming in Java, C, Python or related language.
• Experience with neural and deep learning methods.

Responsibilities

• Collaborate with engineers and scientists to advance multimodal model evaluations.
• Develop and validate automated evaluation methods for perception tasks.
• Analyze large datasets to enhance model capabilities.

Skills

Machine Learning

Data Analysis Skills

Laboratory Experience

Research Experience

Education

PhD in a quantitative field

Tools

Python

Java

Tensorflow

Hadoop

R

Job description

Amazon Devices is an inventive research and development company that designs and engineer high-profile devices like Echo Fire Tablets Fire TV and other consumer devices. We are looking for exceptional scientists to join our Applied Science team to advance the state-of-the-­art in developing efficient multimodal language 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.

The Silicon and Solutions Group Edge AI team is looking for a talented Sr. Applied Scientist who will lead our efforts on inventing evaluation methods for multimodal language models and agents for new 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 framework(s) to support expanding capabilities for multimodal language models
• Analyze large offline and online datasets 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 scientists compiler engineers data collection and product teams to advance evaluation methods
• Mentor less experienced Applied Scientists

A day in the life

As a Scientist with the Silicon and Solutions Group Edge AI team you’ll contribute to innovative methods for evaluating new product experiences and discover ways to enhance our model capabilities and enrich our customer experiences. You’ll research new methods for reliably assessing perception capabilities for audio-visual tasks in multimodal language models design and implement new metrics and develop our evaluation framework. You’ll collaborate across teams of engineers and scientists to identify and root cause issues in models and their system integration to continuously enhance the end-to-end experience.

About the team

Our Edge AI 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 work at the intersection of hardware software and science to build models designed for our custom silicon.

Qualifications

• PhD in engineering technology computer science machine learning robotics operations research statistics mathematics or equivalent quantitative field
• Experience programming in Java C Python or related language
• Experience with neural deep learning methods and machine learning
• Experience in building machine learning models for business application
• Experience with modeling tools such as R scikit-learn Spark MLLib MxNet Tensorflow numpy scipy etc.
• Experience with large scale distributed systems such as Hadoop Spark etc.
• Experience working with evaluations for large language models (LLMs) and / or vision-language models

Key Skills

• Laboratory Experience
• Immunoassays
• Machine Learning
• Biochemistry
• Assays
• Research Experience
• Spectroscopy
• Research & Development
• cGMP
• Cell Culture
• Molecular Biology
• Data Analysis Skills

Employment Type : Full-Time
Experience : years
Vacancy : 1

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