Description

Amazon is investing heavily in building world-class brand shopping experiences to define and deliver a collection of brand shopping products that drive long-term customer value. In particular, Amazon Sponsored Brands (SB) owns a mid-funnel ad product dedicated for brand owners and brand shoppers. We empower brands of all shapes and sizes to attract shoppers in the research and consideration phases of their shopping journey, through visually stunning, inspiring and relevant sponsored shopping experiences. In doing so, we deliver billions of ad impressions and millions of clicks daily, but are only just getting started.

SB Auction team is intended to manage the shopper-Amazon-advertiser tradeoffs at a per-impression level. After ads are sourced, prediction on CTR, VTR, CVR, and relevance score are made, we conduct 3 stages of auction optimization, namely Ranking, Allocation and Pricing.

As a SDE in team, you will drive the scientific and engineering strategy to innovate and build scalable solutions that improve auction design and efficiency. Your work will directly contribute to aligning advertiser needs with customer interests, ensuring that our auction systems maximize relevance and value for all stakeholders. You will contribute to the technical direction of our offerings and solutions, working with many different technologies across the performance advertising organization. You will design, code, troubleshoot, and support scalable machine-learning pipelines and online serving systems. You will work closely with applied scientists to optimize the performance of machine-learning models and infrastructure, and implement end-to-end solutions. What you create is also what you own.

Basic Qualifications

• 3+ years of non-internship professional software development experience

• 1+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience

• Experience programming with at least one software programming language

Preferred Qualifications

• 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience

• 1+ years of big data technologies such as AWS, Hadoop, Spark, Pig, Hive, Lucene/SOLR or Storm/Samza experience

• Experience building complex software systems that have been successfully delivered to customers

• Experience in building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization, or search, 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.

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 $129,300/year in our lowest geographic market up to $223,600/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.