Applied Scientist, Pxt Legends

Amazon Development Centre (Scotland) Limited; City of Edinburgh; Presencial; GBP 70 000 - 110 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

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Resumo da oferta

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.

Qualificações

• 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.

Responsabilidades

• 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.

Conhecimentos

Algorithms and data structures

Statistical analysis

Machine learning experience

Experiment design

Python

Java

C/C++

Formação académica

PhD in a relevant field

Ferramentas

Python

Java

C/C++

Descrição da oferta de emprego

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

• Design and implement machine learning models that power recommendation systems for job seekers and recruiters, ensuring high performance, scalability, and reliability at global scale. Our ideal candidate has a strong scientific foundation and experience of statistical analysis and model building and has a passion for fairness and explainability in ML systems.
• 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.

BASIC QUALIFICATIONS

• 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

PREFERRED QUALIFICATIONS

• Experience in professional software development
• Experience programming or scripting language like Python, Java, C or C++