Principal Reliability Scientist

We are designing the future. If you are in quest of an iterative fast-paced environment, where you can drive innovation through scientific inquiry, and provide tangible benefit to hundreds of thousands of our associates worldwide, this is your opportunity.
Come work on the Amazon Worldwide Fulfillment Design & Engineering Team! We are looking for an exceptional Principal Reliability Engineer, someone that is excited to work on complex real-world challenges for which a comprehensive scientific approach is necessary to drive solutions. Your investigations will include identifying and mitigating reliability risks resulting in design and implementation of safe and reliable fulfillment center designs.
We are seeking a Principal Reliability Scientist who will be responsible to lead reserach specific to reliability for Amazon Fulfillment Facilities.


Key job responsibilities
a. Employing a Failure based approach to develop and implement both analytical and empirical methods for identifying and evaluating reliability risks at the stages of facility design, MHE selection, and deployment.
b. Lead research activities related Design for Reliability (DfR) initiatives for a warehouse, Develop predictive modelling techniques, and test plans.
c. Lead AI-powered reliability solutions that combine data, machine learning, and domain knowledge about asset operations to help anticipate reliability risks, increase uptime, manage CapEx and OpEx costs, and improve productivity.
d. Identifying gaps in current Reliability standards and guidelines, and lead comprehensive research to redefine “industry best practices” based on solid scientific foundations.
e. Continuously strive to gain in-depth knowledge of your profession, as well as branch out to learn about intersecting fields, such as robotics and mechatronics.
f. Travelling to our various sites to perform thorough assessments and gain in-depth operational feedback, approximately 25%-50% of the time.
g. Regular communication with Executive management regarding status, risks and operational program metrics.