Senior Applied Scientist, Machine Learning AcceleratorJob ID: 2791256 | Amazon.com Services LLC
Do you want to join an innovative team of scientists who use deep learning, natural language processing, and large language models to help Amazon provide the best seller experience across the entire Seller life cycle?
Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer interactions every day?
Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real-world problems?
If yes, then you may be a great fit to join the Machine Learning Accelerator team in the Amazon Selling Partner Services (SPS) group.
Key Job ResponsibilitiesThe scope of an Applied Scientist III in the Selling Partner Services (SPS) Machine Learning Accelerator (MLA) team is to research and prototype Machine Learning applications that solve strategic business problems across SPS domains.
Additionally, the scientist collaborates with engineers and business partners to design and implement solutions at scale when they are determined to be of broad benefit to SPS organizations.
They develop large-scale solutions for high impact projects, introduce tools and other techniques that can be used to solve problems from various perspectives, and show depth and competence in more than one area.
They influence the team's technical strategy by making insightful contributions to the team's priorities, approach, and planning.
They develop and introduce tools and practices that streamline the work of the team, and they mentor junior team members and participate in hiring.
BASIC QUALIFICATIONS4+ years of applied research experience3+ 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 learning PREFERRED QUALIFICATIONSExperience 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. 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.
Our inclusive culture empowers Amazonians to deliver the best results for our customers.
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Posted: January 9, 2025
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