Job Description

- PhD, or a Master's degree and experience in CS, CE, ML or related field
- 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


Advertising at Amazon is a fast-growing multi-billion dollar business that spans across desktop, mobile and connected devices; encompasses ads on Amazon and a vast network of hundreds of thousands of third-party publishers; and extends across US, EU and an increasing number of international geographies. The Creative X team has the charter to improve the quality of advertising creatives by detecting and fixing issues in advertiser-supplied creatives, raising the bar on the advertising customer experience.
Our team is looking for Applied Scientists to research and develop the next generation of ML and LLM-based Judge systems that identify and correct issues with advertising creatives. Working with other scientists and engineers, you will bridge the gap between AI research and real-work applications at significant scale. You will provide the science leadership for automatic moderation detections that reduce customer frustration in the screening and remediation of creatives.
Key job responsibilities
o Use statistical analysis, machine learning and LLM techniques to create scalable solutions for business problems
o Analyze and extract relevant information from large amounts of both structured and unstructured data
o Design, experiment and evaluate highly innovative models for regression and classification challenges
o Maintain, evaluate and improve existing models
o Research and implement novel machine learning and statistical approaches
o Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation together with software engineering teams


Experience using Unix/Linux Experience in professional software development


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