Collaborate with engineers, scientists, and product managers to define requirements, create solutions, and deliver products that improve the hiring experience.
Participate in the full software development lifecycle including scoping, design, coding, testing, documentation, deployment, and maintenance of recommendation systems and ML models.
Solve complex ML problems using optimal data structures and algorithms, making thoughtful trade-offs between efficiency and maintainability.
Stay current with scientific literature and develop novel approaches that address business challenges in talent acquisition. You will have the opportunity to provide feedback on scientific work across the organization helping the entire Intelligent Talent Acquisition organization improve.
A day in the life
You might spend the morning reviewing a colleague’s code for a new recommendation algorithm feature, then collaborate with product managers to refine requirements for an upcoming enhancement. After lunch, you’ll dive into model development, analyzing performance metrics from recent A/B tests and implementing improvements to the job-seeker recommendation pipeline. Throughout the day, you’ll participate in scientific discussions with peers across the organization, providing valuable feedback while continuing to refine your expertise.
Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Are enrolled in a PhD in a relevant field
Experience building machine learning models or developing algorithms for business application
Experience in designing experiments and statistical analysis of results
Experience in professional software development
Experience programming or scripting language like Python, Java, C or C++
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Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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