Applied Scientist I (Machine Learning), ITA Automated Performance Evaluation

Amazon

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profile Job Location:

Edinburgh - UK

profile Monthly Salary: Not Disclosed
Posted on: 09-10-2025
Vacancies: 1 Vacancy

Job Summary

Do you want a role with deep meaning and the ability to make a major impact As part of Intelligent Talent Acquisition (ITA) youll have the opportunity to reinvent the hiring process and deliver unprecedented scale sophistication and accuracy for Amazon Talent Acquisition operations. ITA is an industry-leading people science and technology organization made up of scientists engineers analysts product professionals and more all with the shared goal of connecting the right people to the right jobs in a way that is fair and precise. Last year we delivered over 6 million online candidate assessments and helped Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of workers in the right quantity at the right location and at exactly the right time. Youll work on state-of-the-art research advanced software tools new AI systems and machine learning algorithms leveraging Amazons in-house tech stack to bring innovative solutions to life. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in peoples lives. Together we can solve the worlds toughest hiring problems.

Key job responsibilities
As an Applied Scientist you will own the design and development of end-to-end systems. Youll have the opportunity to write technical white papers create technical roadmaps and drive production level projects that will support Amazon Science. You will have the opportunity to design new algorithms models or other technical solutions whilst experiencing Amazons customer focused culture. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems.

About the team
The Automated Performance Evaluation (APE) team is a hybrid team of Applied Scientists and Software Development Engineers who develop deploy and own end-to-end machine learning services for use in the HR and Recruiting functions at Amazon.

- Masters degree in computer science mathematics statistics machine learning or equivalent quantitative field
- Experience programming in Java C Python or related language

- Experience implementing algorithms using both toolkits and self-developed code
- Have publications at top-tier peer-reviewed conferences or journals

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover invent simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( to know more about how we collect use and transfer the personal data of our candidates.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit
for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

Do you want a role with deep meaning and the ability to make a major impact As part of Intelligent Talent Acquisition (ITA) youll have the opportunity to reinvent the hiring process and deliver unprecedented scale sophistication and accuracy for Amazon Talent Acquisition operations. ITA is an indust...
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Key Skills

  • Laboratory Experience
  • Immunoassays
  • Machine Learning
  • Biochemistry
  • Assays
  • Research Experience
  • Spectroscopy
  • Research & Development
  • cGMP
  • Cell Culture
  • Molecular Biology
  • Data Analysis Skills

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