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Applied Scientist, Advertisement Security
4 months ago
Amazon is looking for an Applied Scientist to join the Advertisement Security team in Edinburgh. This team builds scalable solutions that monitor the technical security across Amazon’s advertisement portfolio. Our work is characterized by advanced Machine Learning techniques, high scale, complexity and a constant need for innovation.
The ideal candidate will possess strong machine learning engineering skills and a proven track record of employing cutting-edge machine learning techniques to protect customers from online threats. An expertise in fine-tuning foundational machine learning models across different modalities, as well as knowledge on web security, exposure to internet-scale businesses, working in cross-functional teams, and a track record of peer-reviewed publication in a relevant area are desirable.
As a scientist working at Amazon, you will play a key role in identifying business opportunities, measuring opportunity, inventing and prototyping solutions. You will use a wide range of technologies, programming languages and systems, and work alongside an experienced engineering team. You will have the freedom and encouragement to explore your own ideas and the reward of seeing your contributions benefit millions of customers worldwide.
We are open to hiring candidates to work out of one of the following locations:
Edinburgh, MLN, GBR | London, GBR
BASIC QUALIFICATIONS
- PhD, or a Master's degree and experience in CS, CE, ML or related field research- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience in building machine learning models for business application
PREFERRED QUALIFICATIONS
- Experience using Unix/Linux- Experience in professional software development
