Are you inspired by building new technologies to benefit customers? Do you dream of being at the forefront of and system technology? Would you enjoy working in a fast paced, highly collaborative, start-up like environment? If you answered yes to any of these then you've got to check out the Amazon Scout team.
We've been hard at work developing a new, fully-electric delivery system - Amazon Scout - designed to get packages to customers using delivery devices. These devices were created by Amazon, are the size of a small cooler, and roll along sidewalks at a walking pace. We developed Amazon Scout at our research and development lab in Seattle, ensuring the devices can safely and efficiently navigate around pets, pedestrians and anything else in their path.
The Amazon Scout team shares a passion for innovation using advanced technologies, a love of solving complex challenges, and a desire to impact customers in a meaningful way. We're looking for individuals who like dealing with ambiguity, solving hard, large scale problems, and working in a startup like environment. To learn more about Amazon Scout, check out our Amazon Day One Blog post here: http://amazon.com/scout
Come build the future with us.
Duration: 3 months
Key Job Responsibilities
As a Science Intern, you will work from concept through to execution. This role will give you the opportunity to build tools and support structures needed to analyze , dive deep to resolve root cause of systems errors and changes, and present findings to business partners to drive improvements.
Amazon Scout is currently targeting PhD interns who specialize in , , Deep Learning, , and as it relates to . Basic Qualifications * Enrolled in a PhD degree in Engineering, Science, Machine Learning, Operations Research, Statistics or related fields * Experience in Java, , , R, MATLAB, Python, or similar and programming languages * Experience in design of experiments, statistical analysis, implementing algorithms in using both toolkits and self-developed code * Experience in solving business problems through machine learning, mining and statistical algorithms
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.