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.
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.
Minimum Qualifications Has PhD degree in CS, machine learning, Engineering, Statistics, Operations research, applied math or in a highly quantitative field8+ years of hands-on experience developing and implementing machine learning algorithms and models.Strong demonstrated skills implementing and deploying large scale machine learning applications and tools.Communication and data presentation skills.Strong problem solving ability. Preferred Qualifications Experience in deep learning algorithms/systems.Experience in genAI and LLMs applications.Programming experience in Java/C/C++.Experience using any statistical software package such as Python, R, etc.Experience with the use of Amazon Web Services and cloud computing technologies.Experience with distributed systems for processing large data is a plus.Familiar with Hadoop, Spark, Hive/Pig will be a plus.Ability to handle multiple competing priorities in a fast-paced environment. 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. For individuals with disabilities who would like to request an accommodation, please visit here.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $179,000/year in our lowest geographic market up to $309,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit here. This position will remain posted until filled. Applicants should apply via our internal or external career site.
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