Machine Learning Engineer, Sponsored Products and Brands Full-time

Want to build business and ML systems that impact hundreds of millions of customers Worldwide?

We are looking for outstanding Machine Learning Engineers to join the Kaizen team within Sponsored Products and Brands (SPB). Kaizen team is responsible for growing Amazon Ads business in growing and emerging regions (Asia Pacific, LATAM and EMEA) by defining new regional experiences for shoppers and advertisers based on local context. We own end to end business for SPB and looking for like-minded people who can run with same ownership. As a member of our Agile team you will have the opportunity to drive a key business area in Amazon Ads.

Your team will own the business, technology, and operations, giving you the responsibility and authority to ensure success. You will be involved in every aspect of the process – from idea generation, business analysis and technical design through to software development across a variety of technologies. Your systems will meet remarkably high standards of performance and reliability, and will operate at massive scale, 24×7.

The position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. If you are selected, you have the opportunity to really make a difference to our business by inventing, enhancing and building world class systems, delivering results, working on exciting and challenging projects for our growing businesses.

Key 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.
• Run A/B experiments based on independent data analysis

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

– Bachelors degree in Computer Science or equivalent

PREFERRED QUALIFICATIONS

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

– Have previous experience in Ads tech

– Masters 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. 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 $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.