The host team is developing novel approaches to Anomaly Detection within our Fulfillment Centers. These algorithms are used to detect issues with our equipment before they progress into breakdowns or impact business operations. A variety of data are collected on the equipment, which must be monitored using powerful and scalable solutions.
The postdoc is expected to develop novel algorithms based on Machine Learning that captures and diagnoses these anomalies. Experience with transfer learning and deep learning would be valuable to produce adaptable and scalable solutions.
Key job responsibilities
• Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community.
• Publish your innovation in top-tier academic venues and hone your presentation skills.
• Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise.
• Be comfortable with a fast-paced work with a lot of unknowns and hands-on engagement.
BASIC QUALIFICATIONS
• PhD in a relevant field, received within 2 years of starting the program
• Proven publication record in Statistics or Machine Learning
* Experience with at least one of Anomaly Detection, Transfer Learning, or Deep Learning
PREFERRED QUALIFICATIONS
• Ability to independently deliver results in a fast-paced environment
• Publications at top-tier, peer-reviewed conferences and/or journals
• Exceptional verbal and written communication skills
• Expert knowledge in modeling and performance, operationalization, and scalability of scientific techniques and establishing decision strategies
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