Description

　　Take Earth's most customer-centric company. Mix in hundreds of millions of shoppers spending tens of billions of dollars annually, an exciting opportunity to build next-generation shopping experiences, Amazon’s tremendous computational resources, and our extensive e-Commerce experience. What do you get? The most exciting position in the industry.

　　About our organization:

　　Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers. We run global experiments and our work has revolutionized e-commerce with features such as "Keep shopping for ...", "Tap to explore ...", “Customers who bought this item also bought”, and, “Frequently bought together” among others.

　　Amazon’s internal surveys regularly recognize us as one of the best organizations to work for in the company, with visible high-impact work, low operational load, respectful work-life balance, and continual opportunity to learn and grow.

　　Key job responsibilities

　　As a Sr. Applied Scientist on the team you will lead the roadmap and strategy for applying science to solve customer problems in the Personalization domain. This is an opportunity to come in on Day0 and lead the science strategy of one of the most interesting problem spaces at Amazon - understanding the Amazon customer to build deeply personalized and adaptive shopping experiences. You will be part of a multidisciplinary team, working on one of the largest scale machine learning systems in the company.

　　You will apply your skills in areas such as deep learning and reinforcement learning while building scalable industrial systems. As a member of a highly leveraged team of talented engineers and ML scientists, you will have a unique opportunity to produce and deliver models that help build best-in-class customer experiences and build systems that allow us to deploy these models to production with low latency and high throughput.

　　We are building the next generation of ML systems that power the biggest personalized shopping engine on earth, and we hope you will join us!

　　About the team

　　Our mission is to delight every Amazon customer with a personalized shopping experience. We achieve our mission through investments in large scale machine learning, distributed systems and user experience with the purpose of delivering the future of shopping on Amazon. We are seeking a Senior Applied Scientist to build out adaptive and deeply personalized shopping experiences tailored to the customer's shopping journey.

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

　　New York, NY, USA | San Francisco, CA, USA | Seattle, WA, USA

　　Basic Qualifications

　　3+ years of building machine learning models for business application experience

　　PhD, or Master's degree and 6+ years of applied research experience

　　Experience programming in Java, C++, Python or related language

　　Experience with neural deep learning methods and machine learning

　　Preferred Qualifications

　　Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.

　　Experience with large scale distributed systems such as Hadoop, Spark etc.

　　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 $136,000/year in our lowest geographic market up to $260,000/year 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.