Senior Applied Scientist
1 week ago
About Us
Amazon Development Centre (London) Limited is a leading technology company that powers Amazon's contextual advertising product. We are looking for a skilled Senior Applied Scientist to join our team.
Job Summary
As a Senior Applied Scientist, you will design, prototype, and test machine learning and data science initiatives for contextual data processing and classification. You will collaborate with software engineering teams to integrate successful experiments into large-scale production systems. The ideal candidate will have a PhD in engineering, technology, computer science, or a related quantitative field, and experience in applied research, programming, and building machine learning models for business applications.
About the Team
The Supply Quality organization at Amazon has the charter to solve optimization problems for ad-programs and ensure high-quality ad-impressions. Our team develops advanced algorithms and infrastructure systems to optimize performance for advertisers and publishers. We are focused on solving complex problems in computational advertising, including contextual data processing and classification, traffic quality prediction, security forensics, and viewability prediction.
Responsibilities
* Design, prototype, and test machine learning and data science initiatives for contextual data processing and classification.
* Collaborate with software engineering teams to integrate successful experiments into large-scale production systems.
* Promote the culture of experimentation and applied science at Amazon.
* Meet deadlines while managing multiple projects.
* Communicate and present results effectively with multiple peer groups and different levels of management.
Requirements
* PhD in engineering, technology, computer science, or a related quantitative field.
* Experience in applied research, programming, and building machine learning models for business applications.
* Experience with generative deep learning models and specifically LLM and/or LVM development.
* 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.
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