JobsUSAAI/ML Engineer, Intelligent Talent Acquisition
Company : Amazon
Location : Washington, DC, 20310
Posted Date : 15 September 2025
Job Details
Intelligent Talent Acquisition
Do you want a role with deep meaning and the ability to make a major impact? As part of Intelligent Talent Acquisition (ITA), you'll 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. You'll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms, leveraging Amazon's 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 people's lives. Together, we can solve the world's toughest hiring problems.
Key Job Responsibilities
- Use data science and machine learning to drive business insights, centralizing dashboards, developing and deploying machine learning models, conducting online evaluation and verification of agentic actions.
- Develop AI/ML solutions for Intelligent Talent Acquisition.
- Work closely with engineers, scientists, and product managers to design, implement and launch AI solutions, including Agentic AI, end-to-end.
- Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses.
- Effectively communicate technical and non-technical ideas with teammates and stakeholders.
- Stay up-to-date with advancements and the latest modeling techniques in the field.
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