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Principal Applied Scientist, AWS Identity
Principal Applied Scientist, AWS Identity-March 2024
New York
Mar 29, 2026
ABOUT AMAZON
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10,000+ employees
Technology
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About Principal Applied Scientist, AWS Identity

  Description

  AWS Identity is looking for a passionate, talented, and inventive scientists with a strong machine learning background. We are looking for a scientist to help build transformative solutions to security and access management, by developing state of the technology in machine learning, generative AI and foundational models.

  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 with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).

  About the team

  The team is working on products and services that help customers with access management and security.

  We are open to hiring candidates to work out of one of the following locations:

  New York, NY, USA

  Basic Qualifications

  · 10+ years of relevant, broad research experience after PhD degree or equivalent.

  · Deep expertise in foundational models as well as knowledge of the latest trends in related areas in Machine Learning.

  · Proficiency in programming for algorithm and code reviews.

  · Strong core competency in building solutions

  · Track record of successful projects in algorithm design and product development.

  · Publications at top-tier peer-reviewed conferences or journals.

  · Strong prior experience with mentorship and/or management of senior scientists and engineers.

  Preferred Qualifications

  · PhD in Computer Science, Machine Learning, Mathematics, or related quantitative discipline.

  10+ years of innovative machine learning research experience, with strong analytic and problem-solving skills.

  · 7+ years of experience building and deploying groundbreaking machine learning solutions at scale.

  · Expert level skills across many Machine Learning methodologies.

  · Published peer reviewed papers and journals at top rated academic venues.

  · Experience delivering complex end-to-end global ML solutions that run at very big scale.

  · Experience with access management and security solutions.

  · Effective verbal and written communication skills with non-technical and technical audiences.

  · Experience working with real-world data sets and building scalable models from big data.

  · Experience thinking strategically and with tactical execution.

  · Experience recruiting high caliber talent.

  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 https://www.amazon.jobs/en/disability/us.

  Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $159,100/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 https://www.aboutamazon.com/workplace/employee-benefits. Applicants should apply via our internal or external career site.

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