Applied Scientist, PXT LEGENDS

Amazon Science; City of Edinburgh; Presencial; GBP 70 000 - 110 000; Tempo integral

Resumo da oferta

Amazon Science in Edinburgh is seeking a highly capable ML researcher to design and deploy scalable recommendation systems and ML models for hiring at global scale. You will work with engineers, scientists and product managers to turn research into production-ready software, applying fair and explainable ML methods and contributing to end-to-end system development lifecycle.

The role requires a PhD in a relevant field and strong background in algorithms, statistical analysis and experimentation,

Qualificações

• Experience in algorithms and data structures
• Experience with ML model development for business applications
• Experience designing experiments and statistical analysis of results
• PhD in a relevant field is required or enrollment in a program

Responsabilidades

• Design and implement machine learning models that power recommendation systems at global scale.
• Collaborate with engineers, scientists, and product managers to define requirements and deliver products.
• Participate in full software development lifecycle from scoping to maintenance of ML models.
• Address fairness and explainability in ML systems.
• Stay current with scientific literature and contribute to internal research discussions.

Conhecimentos

Algorithms and data structures

Numerical optimization

Data mining

Parallel and distributed computing

High-performance computing

ML model building

Experiment design

Statistical analysis

Formação académica

PhD in relevant field

Ferramentas

Python

Java

C/C++

Descrição da oferta de emprego

Description

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++

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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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