Do you want to join an cutting-edge team of scientists 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 and deploy advanced ML 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 India Consumer Businesses.
Machine Learning, Big Data and related quantitative sciences have been strategic to Amazon from the early years. Amazon has been a pioneer in areas such as recommendation engines, ecommerce fraud detection and large-scale optimization of fulfillment center operations. As Amazon has rapidly grown and diversified, the opportunity for applying machine learning has exploded.
We have a very broad collection of practical problems where machine learning systems can dramatically improve the customer experience, reduce cost, and drive speed and automation. These include product bundle recommendations for millions of products, safeguarding financial transactions across by building the risk models, improving catalog quality via extracting product attribute values from structured/unstructured data for millions of products, enhancing address quality by powering customer suggestions
We are developing state-of-the-art machine learning solutions to accelerate the Amazon India growth story. Amazon India is an exciting place to be at for a machine learning practitioner. We have the eagerness of a fresh startup to absorb machine learning solutions, and the scale of a mature firm to help support their development at the same time. As part of the India Machine Learning team, you will get to work alongside brilliant min
📌 Applied Scientist II, International Machine Learning (Bengaluru)
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📍 Bengaluru
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