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Senior Applied Scientist

1 month ago

Palo Alto, California, United States Amazon Full time

About Amazon Advertising:

We are a rapidly growing team working to build a unique, world-class advertising group with a relentless focus on the customer. Our mission is to make Amazon the best in class destination for shoppers to discover, engage and build affinity with brands, making shopping beautiful, delightful, and personal.

We focus on enabling Amazon brand ads businesses to align customers' brand shopping intent and brands' unique value. We provide large-scale offline and online Brand Understanding data services, powered by cutting edge Machine Learning technologies.

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.

Key Responsibilities:

  • Building machine learning models for business applications
  • Leading the effort of building key ML features
  • Contributing to the collaborative and innovative spirit within the team
  • Bringing cutting-edge applied research to raise the bar within the team

Requirements:

  • 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

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
  • 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.

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

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Companys reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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 This position will remain posted until filled. Applicants should apply via our internal or external career site.