Description

How can we improve the shopping experience on Amazon.com by tailoring what we display on our pages based on customer interests and preferences? How do we use generative models to help us innovate in different ways to enhance the shopping experience? How do we generate personalized content that helps customers shop at scale?

Our team's stated missions is to "grow each customer’s relationship with Amazon by leveraging our deep understanding of them to provide relevant and timely product, program, and content recommendations." Recommendations at Amazon is a way to help customers discover products. Our team strives to better understand how customers shop on Amazon (and elsewhere) and build recommendations models to streamline customers' shopping experience by showing the right products at the right time. Understanding the complexities of customers' shopping needs and helping them explore the depth and breadth of Amazon's catalog is a challenge we take on every day.

Using Amazon’s large-scale computing resources, your team will build and deploy text and generation models that help customers shop on Amazon. You will ask research questions about customer behavior, develop state-of-the-art models that improve shopping features, and deploy these models to production. You will participate in the Amazon ML community and mentor Applied Scientists and software development engineers with a strong interest in and knowledge of ML and generative AI. Your team's work will directly benefit customers and the retail business.

We are looking for a passionate, hard-working, and talented Applied Science Manager who has experience building mission critical teams that design and deploy data-driven applications that customers love. You will have an opportunity to innovate and execute on an ambitious vision for generative AI and science initiatives that improve the everyday lives of millions of people.

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

Seattle, WA, USA

Basic Qualifications

• 3+ years of scientists or machine learning engineers management experience

• Knowledge of ML, NLP, Information Retrieval and Analytics

• Experience directly managing scientists or machine learning engineers

• Experience communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs

• Experience with the Scrum methodology (or similar alternatives) for agile software development

• Experience in applied research

• Experience hiring and growing top talent

Preferred Qualifications

• Experience building machine learning models or developing algorithms for business application

• Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers

• Experience building complex highly-scalable systems that involve predictive models or applications of machine learning

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 $147,100/year in our lowest geographic market up to $286,000/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. This position will remain posted until filled. Applicants should apply via our internal or external career site.