Be part of a team that is driving the expansion of Amazon globally. The Recruiting Technologies team is responsible for the architecture, design, implementation and delivery of systems that touch the entire organization.
We are creating an industry leading candidate experience; developing, building, and innovating global, scalable technology recruiting solutions that are intelligent, powerful and light-weight. This team and technologies are a critical component in Amazon's continued growth and launching of new products and services.
As a member of the Machine learning team you will contribute at the forefront of cutting edge machine learning. You will develop and evaluate machine learning models using large data-sets, cloud services and listening to customers behavior to improve the recruiting experiences. You will help us push the limits of technology as we build personalized recommendations. You will have the opportunity to apply a variety of machine learning algorithms including deep learning neural networks, and work on one of the world's largest data sets to influence the long term evolution of our technology roadmap. We are looking for customer obsessed machine learning scientists who can apply the latest research, state of the art algorithms and machine learning to build highly scalable recommendation and personalization systems, as well as tackle content classification problems.BASIC QUALIFICATIONS
• PhD in Mathematics, Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field.
• 4+ years of practical experience applying ML to solve complex problems.
• Algorithm and model development experience for large-scale applications.
• Hands-on experience using Java, C++, or other programming language, as well as with R, MATLAB, Python or similar scripting language.
• Knowledge in Statistics, machine learning, predictive modelling, data mining.PREFERRED QUALIFICATIONS
• Improve and accelerate our technology with science, statistical modeling, algorithm design, and prototyping.
• Maintain an understanding of industry and technology trends in said area of research.
• Extensive knowledge and practical experience in deep neural networks and other recommendation systems, including: convolutional neural networks (CNNs), recurrent neural networks (RNNs), residual neural networks and collaborative or content filtering techniques.
• Experience building robust metrics for machine learning performance evaluation, A/B testing, statistical evaluation of experimental data, etc.
• Research and implement novel machine learning and statistical approaches.
• Ability to take a project from scoping requirements through actual launch of the project.
• Excellent written and verbal communication skills.
• Strong peer reviewed scientific contributions in premier journals and conferences.
Amazon is an Equal Opportunity-Affirmative Action Employer - Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation