Applied Scientist, Amazon Prime, Prime AI/ML Science
Amazon - Seattle, Washington, USA
Posted Apr 16, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
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- Salary
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- 401(k) match
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Schedule
- Shift type
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
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Where they hire
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About this role
Applied Scientist, Amazon Prime, Prime AI/ML Science Seattle, Washington, USA Interested in modeling and understanding customer behavior through machine learning, artificial intelligence, and data mining over TB scale data with huge business impact on millions of customers? Join our team of Scientists and Engineers developing models to predict customer behavior and optimize the customer experience with Amazon Prime. This includes identifying who our customers are, modeling customer behavior, and creating personalization systems to optimize the experience. As an ML expert, you will partner directly with product owners to intake, build, and directly apply your modeling solutions. There are numerous scientific and technical challenges you will get to tackle in this role, such as global scalability of models, combinatorial optimization, cold start problem, accelerated experimentation, short/long term goals modeling, GenAI based content creation, foundation modeling, and multi-step optimization leading to reinforcement learning of the customer journey. We employ techniques from GenAI, LLMs, deep learning, supervised learning, bandits, optimization, and RL. As the central science team within Prime, our expertise gets routinely called upon to weigh in on a variety of topics. We also emphasize the need and value of scientific research and have developed a strong publication and patent record (internally/externally) which you will be a part of. You will also utilize and be exposed to the latest in AI/ML technologies and infrastructure: AWS technologies (EMR/Spark, Redshift, Sagemaker, DynamoDB, S3, ...), various AI/ML algorithms and techniques (GenAI, LLMs, transformers, sequential models, Neural Networks, supervised/unsupervised/semi-supervised/reinforcement learning), and statistical modeling techniques. Major responsibilities
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