Description

　　This internship position is reserved for students that have been awarded an Amazon Student Fellowship

　　Have you been awarded an Amazon Student Fellowship in the areas of AI and Machine Learning? We are looking for skilled scientists capable of putting AI and Machine Learning theory into practice through experimentation and invention, leveraging machine learning techniques (such as random forest, Bayesian networks, ensemble learning, clustering, etc.), and implementing learning systems to work on massive datasets in an effort to tackle never-before-solved problems.

　　A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to create technical roadmaps, and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems.

　　Amazon Science gives insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists use our working backwards method to enrich the way we live and work.

　　For more information on the Amazon Science community please visit https://www.amazon.science.

　　To ensure a great internship experience, please keep these things in mind. This is a full-time internship and requires an individual to work 40 hours a week for the duration of the internship. Amazon requires an intern to be located where their assigned team is. Amazon is happy to provide relocation and housing assistance if you are located 50 miles or further from the office location.

　　We are open to hiring candidates to work out of one of the following locations:

　　Arlington, VA, USA | Boston, MA, USA | New York, NY, USA | Palo Alto, CA, USA | Seattle, WA, USA

　　Basic Qualifications

　　• Awarded an Amazon Student Fellowship

　　• Enrolled in a Ph.D. degree in computer science, machine learning, engineering, or related fields.

　　• Experience in designing experiments and statistical analysis of results.

　　• Experience in understanding and ability to implement algorithms using both toolkits and self-developed code.

　　• Experience with Java, C++, or other programming language, as well as with R, MATLAB, Python, or similar scripting language.

　　Preferred Qualifications

　　• Technical fluency; comfort understanding and discussing architectural concepts and algorithms, schedule tradeoffs and new opportunities with technical team members.

　　• Publication(s) at peer-reviewed conferences or journals.

　　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.

　　Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $65.38/hr in our lowest geographic market up to $106.83/hr in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. Applicants should apply via our internal or external career site.