Software Development Engineer - Machine Learning, Sponsored Products

- 3+ years of non-internship professional software development experience
- 2+ 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
- Experience building complex software systems that have been successfully delivered to customers
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
- Experience in machine learning, data mining, information retrieval, statistics or natural language processing

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.
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

Does serving ads to billions of search requests daily and finding the most relevant ads for a search page from billions of ads in 10s of milliseconds excite you?
The Sponsored Products Search Relevance team owns identifying the relevant ads to surface to customers when they search for products on Amazon. We strive to understand our customers’ intent and identify relevant ads which enable them to discover new and alternate products. This also enables sellers on Amazon to showcase their products to customers, which may at times be buried deeper in the search results.
Our systems and algorithms operate on one of the world's largest product catalogs, matching shoppers with products - with a high relevance bar and strict latency constraints. We are a team of machine learning scientists and software engineers working on complex solutions to understand the customer intent and present them with ads that are not only relevant to their actual shopping experience, but also non-obtrusive. This area is of strategic importance to Amazon Retail and Marketplace business, driving long term-growth.

We are looking for a SDE - Machine Learning who can drive appropriate technology choices for the business, lead the way for continuous innovation, and shape the future of ad serving on Amazon search. You will build services to handle billions of requests per day, while maintaining response latency in milliseconds and meeting strict SLA requirements. It is quite routine for our systems to operate on massive datasets using distributed frameworks. You will design and code, troubleshoot, and support high volume and low latency distributed systems. The solutions you create would ensure relevant ads are served to Amazon's customers. You will directly impact our customers’ shopping experience while helping our sellers get the maximum ROI from advertising on Amazon. This role will provide exposure to cutting-edge innovations in product search, information retrieval, natural language processing (NLP), LLM training, deep learning, and image processing. In addition to being a strongly motivated IC, you will also be responsible for mentoring junior engineers and guiding them to deliver high impacting products and services for Amazon customers and sellers.


Key job responsibilities
Job Responsibilities:

• Drive the direction of our technical solutions, and work on many different technologies such as deep learning, AWS, Auto ML, real-time ML serving systems.
• Design, develop, and production software to support scalable offline machine-learning pipelines and online serving components.
• Work closely with applied scientists to optimize the performance of machine-learning models, improve the team’s machine learning productivity, and advance the technical foundation to empower our science innovation. What you create is also what you own.