Principal Applied Scientist, Amazon at Amazon
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Join an innovative team of scientists and engineers who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon's customers.
Key job responsibilities
“Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.”
Please visit https://www.amazon.science for more information
Do you want to join an innovative team of scientists and engineers who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon's customers? Do you want to build advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning team for our International Consumer Businesses. The team builds the next generation of Machine Learning solutions for a wide spectrum of problems by leveraging generative-AI and LLMs, in areas such as Recommendations, Search Relevance, Catalog Quality, Online Ads, Pricing, Demand/Forecasting, Computer Vision, and Conversational Systems.
A day in the life
Build advanced algorithmic systems that help optimize millions of transactions every day.
About the team
The team builds the next generation of Machine Learning services for a wide spectrum of problems in areas such as Recommendations, Search Relevance, Computer Vision, Catalog Quality, Online Ads, Pricing, Demand/Forecasting, and Conversational Systems.
Key job responsibilities
“Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.”
Please visit https://www.amazon.science for more information
Do you want to join an innovative team of scientists and engineers who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon's customers? Do you want to build advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning team for our International Consumer Businesses. The team builds the next generation of Machine Learning solutions for a wide spectrum of problems by leveraging generative-AI and LLMs, in areas such as Recommendations, Search Relevance, Catalog Quality, Online Ads, Pricing, Demand/Forecasting, Computer Vision, and Conversational Systems.
A day in the life
Build advanced algorithmic systems that help optimize millions of transactions every day.
About the team
The team builds the next generation of Machine Learning services for a wide spectrum of problems in areas such as Recommendations, Search Relevance, Computer Vision, Catalog Quality, Online Ads, Pricing, Demand/Forecasting, and Conversational Systems.