Do you want to join an innovative team of scientists who use machine learning and statistical techniques to keep Amazon the safest and most trusted place to shop online? Are you excited by the prospect of analyzing and modeling terabytes of data and create state-of-art algorithms to solve real-world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Amazon Machine Learning Science group for an internship in 2019.
- Use statistical and machine learning techniques to create scalable object recognition and text understanding systems
- Design, development and evaluation of highly innovative models for training and prediction
- Working closely with software engineering teams to drive real-time model implementations and new feature creations
- Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
- Tracking general business activity and providing clear, compelling management reporting on a regular basis
- Research and implement novel machine learning and statistical approaches
- A Ph.D. student in Computer Science, Machine Learning, Statistics, Operational Research, or in a highly quantitative field
- Hands-on experience in predictive modeling and analysis
- Experience in Python or Java/Scala programming
- Communication and data presentation skills
- Problem-solving ability
- Experience with neural network toolkits
- Publications in top-tier ML conferences and journals
- Experience with Spark, Hadoop, or other distributed systems
Sounds interesting? We look forward to your application. Please apply online and upload your CV and a letter of motivation in one document (max. 5 MB).
By submitting your resume and application information, you authorize Amazon to transmit and store your information in the Amazon group of companies' world-wide recruitment database, and to circulate that information as necessary for the purpose of evaluating your qualifications for this or other job vacancies.