We're looking for an experienced Applied Scientist with exceptional technical, analytical, and innovative capabilities to research, design, and create elegant machine learning solutions. Your solutions will help our advertisers with multi-media and multi-lingual advertising offerings, leveraging Generative AI, Deep Neural Networks, Natural Language Processing (NLP), and Computer Vision (CV). You will build ML models that localize multi-media advertising contents, including text, images and videos. You will also identify opportunities to leverage ML beyond localization, including, international expansion and global advertising. Your work will directly impact our customers in the form of products and services used directly by our advertisers as well as our third-party integrators.

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. Our products are strategically important to our businesses driving long term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

The Advertiser Growth Engine (AGE) team owns and builds services and applications across Amazon World-Wide Advertising that make advertising across countries/languages as easy as flipping a switch. We are focused on: (1) expanding Amazon Ads advertiser base, and (2) eliminating localization, operational, and marketplace knowledge gap barriers for Advertisers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth globally.

Key job responsibilities
As an Applied Scientist on this team, you will:
- Build and deliver end-to-end machine learning solutions; build ML models and perform data analysis to deliver scalable solutions to business problems.
- Work closely with senior leaders across science, engineering, and product disciplines to drive the team's roadmap and establish business requirements.
- Perform hands-on analysis and modeling with enormous data sets to develop insights that increase traffic monetization and merchandise sales without compromising shopper experience.
- Run A/B experiments that affect hundreds of millions of customers, evaluate the impact of your optimizations and communicate your results to various business stakeholders.
- Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
- Research new innovate machine learning approaches.

BASIC QUALIFICATIONS

- 5+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

PREFERRED QUALIFICATIONS

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy 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. 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 $150,400/year in our lowest geographic market up to $260,000/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.