Description

　　The Amazon Shopper Panel is an opt-in, invitation-only program where participants can earn monthly rewards by sharing receipts from purchases made outside of Amazon and answering surveys. The program provides immediate rewards to participants who choose to join the panel, and will benefit all of our customers in the form of better shopping, product, and advertising experiences. It also helps advertisers understand how their ads support their sales at other retailers – and through panel surveys, helps them improve their products and grow their businesses. As part of the Amazon Shopper Panel team, you will help build powerful and exciting features that will accelerate the adoption of the Amazon Shopper Panel mobile app. You can learn more about our program at panel.amazon.com

　　Amazon Advertising operates at the intersection of e-Commerce 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 reach Amazon customers across our owned and operated sites, on other high-quality sites across the web, and on millions of Kindles, streaming services, and 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!

　　Key job responsibilities

　　As a Machine Learning Engineer II at Amazon, you will drive appropriate technology choices for the business, lead the way for continuous innovation, and shape the future of advertising and e-commerce. You will design, implement, troubleshoot machine learning models in the field of NLP and computer vision and see your solutions live.

　　A Machine Learning Engineer (MLE) is a Software Development Engineer (SDE) with focus on Machine Learning (ML) applications. The MLE should have a broad understanding of the standard fundamental ML concepts, techniques, when and how to apply them. The MLE should also be adept in using modern ML and cloud technologies such as AWS, SageMaker, Pytorch, Hugging Face, Docker, etc.

　　The MLE will collaborate with product managers or technical program managers, machine learning scientists and other SDEs to develop, deploy, and maintain services that implement a wide range of machine learning models to solve problems related to natural language processing, computer vision, and numerical analysis.

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

　　New York, NY, USA

　　Basic Qualifications

　　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

　　Preferred Qualifications

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

　　Master's degree in computer science or equivalent

　　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 $115,000/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. Applicants should apply via our internal or external career site.