Calling all PhD students passionate about machine learning! We are looking for skilled scientists who can transform theory into groundbreaking reality. Join us in revolutionizing the field by harnessing the power of machine learning techniques like random forest, Bayesian networks, ensemble learning, and clustering. Dive into massive datasets and conquer unprecedented challenges with your innovative learning systems. Don’t miss this opportunity to make history and solve problems that have never been cracked before!
We are seeking a candidate who thrives in dynamic environments, embraces uncertainty, and possesses a meticulous eye for detail. As an Applied Science Intern, you will take charge of designing and building comprehensive systems from start to finish. This role offers the chance to craft technical roadmaps and spearhead projects of significant impact, bolstering the efforts of Amazon Science. Collaborating closely with Amazon scientists and fellow interns, you will develop innovative solutions and seamlessly implement them into production. The ideal scientist will excel in collaborating with diverse groups and cross-functional teams to tackle intricate business challenges.
Amazon Science offers a glimpse into the company’s commitment to customer-obsessed scientific innovation. At Amazon, we firmly believe that scientific breakthroughs are crucial to being the worlds most customer-centric company. It is our ability to make a significant impact on a global scale that enables us to attract the brightest minds in artificial intelligence and related fields. Our scientists employ the use our working backwards approach to revolutionize the way we live and work, constantly enriching our lives with their groundbreaking discoveries.
For more information on the Amazon Science community please visit https://www.amazon.science.
We are open to hiring candidates to work out of one of the following locations:
Arlington, VA, USA | Bellevue, WA, USA | Boston, MA, USA | New York, NY, USA | Palo Alto, CA, USA | San Diego, CA, USA | Santa Clara, CA, USA | Seattle, WA, USA
• 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.
• 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.
• Excellent critical thinking skills, combined with the ability to present your beliefs clearly and compellingly in both verbal and written form.
Amazon has positions available for Machine Learning intern positions located in but not limited to Arlington, VA; Bellevue, WA; Boston, MA; New York, NY; Palo Alto, CA; San Diego, CA; Santa Clara, CA; Seattle, WA.
Pursuant to the Los Angeles and San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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.