Amazon Development Center U.S., Inc.
Senior Applied Scientist, AWS Identity
Amazon Development Center U.S., Inc., Bellevue, Washington, us, 98009
Job ID: 2751298 | Amazon Development Center U.S., Inc.The Automated Reasoning & Identity Science team at AWS is looking for a passionate, talented, and inventive scientist with a strong machine learning background. In this role, you will help build transformative solutions for security and access management, by developing state of the technology in machine learning, generative AI and foundational models. Your experience with anomaly detection, classification systems, model development and fine tuning will set you up for success in this role.
Key Job Responsibilities
You will define the scientific roadmap, identify relevant data, propose innovative machine learning solutions, conduct rigorous experiments, publish results, and work with the engineering team to deploy these solutions.You will identify investment opportunities, develop long term strategies, and propose, prioritize, and deliver on goals. You’ll also participate in organizational planning, hiring, mentorship, and leadership development. You will be technically fearless and passionate about building scalable science and engineering solutions. You will serve as a scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).
About the Team
The Automated Reasoning & Identity Science team is working on products and services that help customers with access management and security and partner with science teams in AWS Identity and Amazon GuardDuty.
BASIC QUALIFICATIONS
3+ years of building machine learning models for business application experienceExperience programming in Java, C++, Python or related languagePhD, or Master's degree and 6+ years of applied research experience
PREFERRED QUALIFICATIONS
Experience with neural deep learning methods and machine learningExperience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
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.
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Key Job Responsibilities
You will define the scientific roadmap, identify relevant data, propose innovative machine learning solutions, conduct rigorous experiments, publish results, and work with the engineering team to deploy these solutions.You will identify investment opportunities, develop long term strategies, and propose, prioritize, and deliver on goals. You’ll also participate in organizational planning, hiring, mentorship, and leadership development. You will be technically fearless and passionate about building scalable science and engineering solutions. You will serve as a scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).
About the Team
The Automated Reasoning & Identity Science team is working on products and services that help customers with access management and security and partner with science teams in AWS Identity and Amazon GuardDuty.
BASIC QUALIFICATIONS
3+ years of building machine learning models for business application experienceExperience programming in Java, C++, Python or related languagePhD, or Master's degree and 6+ years of applied research experience
PREFERRED QUALIFICATIONS
Experience with neural deep learning methods and machine learningExperience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
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.
#J-18808-Ljbffr