Senior Applied Scientist

4 weeks ago

London, Greater London, United Kingdom Amazon Development Centre (London) Limited Full time
About the Role

Amazon Advertising is seeking a highly skilled Senior Applied Scientist to join its team and contribute to the development of cutting-edge contextual advertising solutions. As a key member of our team, you will be responsible for designing, prototyping, and testing innovative machine learning and data science initiatives that power our contextual advertising product.

Key Responsibilities
  • Design and develop machine learning models for contextual data processing and classification
  • Collaborate with software engineering teams to integrate successful experiments into large-scale production systems
  • Promote a culture of experimentation and applied science within Amazon
  • Develop and maintain high-quality algorithms and infrastructure systems for ad-program optimization
  • Work closely with cross-functional teams to solve complex optimization problems in computational advertising
About the Team

The Supply Quality organization at Amazon is responsible for solving optimization problems for ad-programs and ensuring high-quality ad-impressions. Our team includes experts in distributed computing, machine learning, statistics, optimization, text mining, information theory, and big data systems. We are focused on solving a wide range of problems in computational advertising, including contextual data processing and classification, traffic quality prediction, security forensics, viewability prediction, and brand safety.

Requirements
  • PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or equivalent quantitative field
  • Experience in applied research and machine learning model development
  • Experience with generative deep learning models and specifically LLM and/or LVM development
  • Strong programming skills in Java, C++, Python, or related languages
  • Experience with large-scale distributed systems and machine learning frameworks
Preferred Qualifications
  • 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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