Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.
The Ad Response Prediction team in Sponsored Products organization build advanced deep-learning models, large-scale machine-learning (ML) pipelines, and real-time serving infra to match shoppers’ intent to relevant ads on all devices, for all contexts and in all marketplaces. Through precise estimation of shoppers’ interaction with ads and their long-term value, we aim to drive optimal ads allocation and pricing, and help to deliver a relevant, engaging and delightful ads experience to Amazon shoppers. As the business and the complexity of various new initiatives we take continues to grow, we are looking for energetic, entrepreneurial, and self-driven science leaders to join the team.
Key job responsibilities
As a Principal Applied Scientist in the team, you will:
- Seek to understand in depth the Sponsored Products offering at Amazon and identify areas of opportunities to grow our business via principled ML solutions.
- Mentor and guide the applied scientists in our organization and hold us to a high standard of technical rigor and excellence in ML.
- Design and lead organization wide ML roadmaps to help our Amazon shoppers have a delightful shopping experience while creating long term value for our sellers.
- Work with our engineering partners and draw upon your experience to meet latency and other system constraints.
- Identify untapped, high-risk technical and scientific directions, and simulate new research directions that you will drive to completion and deliver.
- Be responsible for communicating our ML innovations to the broader internal & external scientific community.
We are open to hiring candidates to work out of one of the following locations:
Palo Alto, CA, USA
- PhD in Computer Science, Statistics or related field.
- 10+ years of applied ML experience in deploying ML solutions to customer facing products.
- 2+ years hands-on experience leading multiple ML teams to design products that satisfy a customer need.
- Track record of delivering large-scale and high-quality ML solutions.
- Experience in taking on & using ML to deliver on business goals.
- Experience in shipping large-scale deep learning models for online recommendation, personalization, or search.
- Experience partnering with engineering teams to ensure deep learning solutions meet latency requirements.
- Experience in influencing product strategy through cutting edge research in deep learning.
- Evidence of producing internal or external publications that motivate new lines of research.
- Excellent verbal and written communication.
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 $159,100/year in our lowest geographic market up to $309,400/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.