Applied Scientist, Talent AI for Fair Hiring

Amazon Development Centre (Scotland) Limited; City of Edinburgh; On-site; GBP 70,000 - 110,000; Full time

Benefits offered by this job

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Job summary

Amazon Development Centre (Scotland) Limited seeks a PhD-level candidate to design and implement ML-based recommendation systems. You will collaborate with engineers, scientists, and product managers to translate requirements into scalable solutions and contribute to the full ML lifecycle from design to deployment.

You will stay current with literature and help advance fairness and explainability in ML as part of ITA, impacting hiring operations at scale.

Qualifications

• Experience in algorithms, data structures, numerical optimization, data mining, parallel and distributed computing, or 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.

Responsibilities

• Design and implement machine learning models that power recommendation systems for job seekers and recruiters at global scale.
• Collaborate with engineers, scientists, and product managers to define requirements and deliver products.
• Participate in full software development lifecycle including scoping, design, coding, testing, deployment and maintenance of models.
• Solve complex ML problems using efficient data structures and algorithms with trade-offs between performance and maintainability.
• Stay current with scientific literature and contribute feedback on scientific work across ITA.

Skills

Algorithms and data structures

Statistical analysis

Machine learning experience

Experiment design

Python

Java

C/C++

Education

PhD in a relevant field

Tools

Python

Java

C/C++

Job description

Amazon Development Centre (Scotland) Limited seeks a PhD-level candidate to design and implement ML-based recommendation systems. You will collaborate with engineers, scientists, and product managers to translate requirements into scalable solutions and contribute to the full ML lifecycle from design to deployment.

You will stay current with literature and help advance fairness and explainability in ML as part of ITA, impacting hiring operations at scale.