Research Scientist - AWS Identity & Access

Job ID: 1069486 | Amazon Dev Center U.S., Inc.


The Amazon Web Services (AWS) Identity team innovates, builds, and operates the identity, authentication, and authorization stack for the AWS cloud. Our mission is to push technical boundaries and enable AWS customers to run their business workloads confidently and securely. We rely on large scale data analysis techniques including machine learning and automated reasoning to help customers set access controls across all their AWS environments. These tools help customers set the right access controls for their AWS environments without needing to become security experts.

As a research scientist in AWS Identity you will innovate on behalf of AWS customers to develop and deliver functionalities through innovation and experimentation. You will identify and research areas of interest, including recommendation systems, deep learning, forecasting, and clustering. You will build machine learning models that rely on big data to provide recommendations to help customers set the right access controls. You demonstrate best practices to evaluate, test, and compare models and the systems that use them. You will collaborate with product owners, developers, and customers to identify and define areas where machine learning can enhance the customer experience.


· MS or PhD in Computer Science, Machine Learning, Math, Statistics or equivalent.
· MS + 4 years of experience, or PhD + 1 year experience.
· Experience deploying predictive models to serve customers in production environments.
· Depth in the methods and applications for at least one application of machine learning such as Computer Vision (CV), Natural Language Processing (NLP), collaborative filtering, forecasting, or personalization.
· 2 + years experience programming with Python.
· Experience with modeling tools such as MXNet, PyTorch, Keras, numpy, and scipy to develop and deliver models.
· Competency programming in Scala, Java, C/C++ or similar languages.


· Experience with big data tools such Spark and Hadoop to horizontally scale processing to millions of records as part of an end-to-end ML pipeline.
· Experience developing practical algorithms that deliver business impact.
· Executing, documenting and presenting data analysis.
· Familiar with theory of information retrieval, machine learning, convex optimization, and data mining.
· Experience using AWS EMR, Amazon SageMaker, and other AWS services as part of functional end-to-end systems.
· Excellent communication skills, both written and oral with both technical and business people.

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