DESCRIPTION

Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of advertising tools within Sponsored Products and Sponsored Brands that drive discovery and advertiser growth. Our brand understanding products are strategically important to our advertisers, helping them propel long term growth across retail and marketplace businesses. We deliver billions of ad impressions and clicks daily and are breaking fresh ground to create world-class brand intelligence models and products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action.

Within Sponsored Ads Advertiser Growth organization, the Brand Intelligence team is on a mission to make Amazon the best in class destination for shoppers to discover, engage and build affinity with brands, thereby making shopping delightful, and a personalized experience. Our team builds the central brand understanding foundation for Amazon ads and beyond. We focus on enabling brands to align customers’ shopping intent and position its unique value proposition via Amazon Ads. We provide large-scale offline and online brand understanding data services, powered by cutting edge Machine Learning technologies (e.g., Large-Language-Model, Multi-Modal Deep Neural Networks, Statistical Modeling).

About this Role:
We are looking for a passionate, talented Senior Applied Scientist in the field of Natural Language Processing (NLP), Computer Vision (CV), Large Language Model (LLM), Ads Recommender Systems, and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware Brand Understanding. A successful candidate will have strong machine learning background and a desire to push the boundary of one or more of the above areas. The ideal candidate is expected to leading the effort of building key ML features, contribute to the collaborative and innovative spirit within the team, and bring cutting-edge applied research to raise the bar within the team.

BASIC QUALIFICATIONS

– 3+ 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
– Experience in building machine learning models for business application

PREFERRED QUALIFICATIONS

– Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
– Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)
– Experience with large scale distributed systems such as Hadoop, Spark etc.
– Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
– Published relevant research work in leading ML conferences or journals.

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.

USA, WA, Seattle