Job Description

Director, Applied Science, Selling Partner Recruitment and Success

We’re seeking a thought leader to direct Advanced ML initiatives aimed at scaling our $600B+ Amazon ecommerce business.

This person will also be a deep learning practitioner/thinker and guide the research in these areas. They’ll have the ability to drive cutting edge, product-oriented research and should have a notable publication record.

This intellectual thought leader will help enhance the science in addition to developing the thinking of our team. This leader will build / develop the team, direct and shape the science philosophy, and plan / strategize, as we explore domains such as reinforcement learning (RL), optimization, simulation, and leading technology in Large Language Models (LLMs) to facilitate seller recruiting, onboarding, growth, and brand building.

Joining this team, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of Amazon [Earth's most customer-centric internet company].

About the team
Selling Partner Recruitment and Success (SPRS) builds the programs, tools, systems, and science to recruit new selling partners with valuable selection into Amazon’s stores, drive their engagement with Amazon’s selling programs and services, and empower them to realize their potential for success and sustainable growth in our stores. We use advanced ML techniques to help scale the growth and success of sellers, who contribute over 60% of the sales for Amazon’s e-commerce business. The application of ML in this area is a relatively new focus for our business, and the opportunity is huge!

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

Seattle, WA, USA

Minimum Qualifications:
- Advanced degree (PhD) in computer science, statistics, engineering, mathematics or related discipline.
- Experienced leader of leaders, with 10+ years of experience managing multiple science and/or engineering teams.
- 10+ years of experience building and applying ML models to solve complex problems for large-scale applications and staying current with the latest science e.g. deep Learning models and Generative AI.
- Experience with leadership of experienced scientists as well as a record of developing junior scientists for a career track in a business environment.
- Familiar with one or more programming languages.
- Combination of deep technical skills and business savvy enough to interface with all stakeholders directly.
- Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to research scientists, engineering teams and business audiences.
- Experience implementing algorithms, tailored to business needs and tested on large data sets.
- Strong research track record.
- Experience with a broad range of ML systems such as personalized recommendations, forecasting and developing generative AI solutions.

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

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $262,500/year in our lowest geographic market up to $350,000/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 This position will remain posted until filled. Applicants should apply via our internal or external career site. #J-18808-Ljbffr

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