Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital display advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers of all types to reach Amazon customers on Amazon.com, across our other owned and operated sites, on other high quality sites across the web, and on millions of mobile devices. We start with the customer and work backwards in everything we do, including advertising. If you’re interested in joining a rapidly growing team working to build a unique, world-class advertising group with a relentless focus on the customer, you’ve come to the right place.
About our team:
SPB Brand Identity Team is on a mission to make Amazon the best in class destination for all brand needs. Our team builds a centralized brand identity datastore responsible for creating brands, mapping advertisers, products, and ads to brands. This enables our advertisers and customers to tell engaging brand stories through mappings generated and delivered by our team. We also enables customer-brand engagement enhancement through a UI allowing advertisers to self-manage and correct any mappings. Together these mappings are used by dozens of internal teams to generate measurement reports, brand intelligence, similar brands (i.e. substitutes), shopper/brand signals, etc.
About this Role:
We are looking for a passionate, talented Applied Scientist in the field of Natural Language Processing (NLP), Large Language Model (LLM), Ads Recommender Systems, Data Mining and Feature Engineering, and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware Brand Understanding. A successful candidate will have strong machine learning background and a desire to push the boundary of one or more of the above areas. The ideal candidate is expected to leading the effort of building key ML features, contribute to the collaborative and innovative spirit within the team, and bring cutting-edge applied research to raise the bar within the team.
BASIC QUALIFICATIONS
- 3+ years of building models for business application experience
- PhD, or Master's degree and 3+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
PREFERRED QUALIFICATIONS
- Experience using Unix/Linux
- Experience in professional software development
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.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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 $222,200/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.