Job ID: 2610631 | Amazon.com Services LLC
As a Senior Applied Scientist in Worldwide Defect Elimination at Amazon, your role is pivotal in leveraging advanced AI and ML techniques to address customer issues at scale. You'll lead the development of innovative solutions that summarize and detect problems, organize them using ontologies, and pinpoint root causes within Amazon systems. Your expertise will drive the identification of responsible stakeholders and enable swift resolution. You will utilize the latest in AI/ML to develop an LLM ecosystem that can comb over our billions of contacts (using a combination of media). As a part of this role, you will collaborate with a large team of experts in the field and move the state of research forward.
Key job responsibilitiesResearch and Development of Cutting Edge Modeling techniques for NLP, NLU, and Prediction.Establishing scientific culture and standards for all the scientists (publication, best practices, reviews, etc.)Delivering solutions to the core business problems above and influencing business partnersDevelop scientific talent on the teamA day in the lifeIf you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!
BASIC QUALIFICATIONS5+ years of building machine learning models for business application experiencePhD, or Master's degree and 6+ years of applied research experienceExperience programming in Java, C++, Python or related languageExperience with neural deep learning methods and machine learningPREFERRED QUALIFICATIONSExperience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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