The Amazon Search team creates customer-focused search solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, our services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day.
Within Amazon Search, the Relevance team has a mission to solve customer problems that require advancing the state of the art in retrieval and ranking. We work backwards from the customer to create value for them by addressing an underlying, unsolved scientific problem. We deploy our solutions through distributed systems that operate at millisecond latencies at Amazon scale. We strive to publish our solutions and open-source our software so that the broader scientific community can benefit.
As a Sr. Applied Scientist on our team, your role is to leverage your strong background in Computer Science and Deep Learning to help build models that shrink hundreds of thousands of retrieved matches to the few hundred that are subject to the final stage ranking. This role requires a pragmatic technical leader comfortable with ambiguity, capable of summarizing complex data and models through clear visual and written explanations. The ideal candidate will have experience with deep learning models and information retrieval/recommendation systems at scale.
The Relevance team operates out of Amazon's Palo Alto and Seattle offices. You will have an opportunity to influence our goals and mission. Your solutions will impact all of Amazon's retail customers. We are a mix of applied scientists and software engineers who collaborate with other teams within Amazon Search to solve and deploy deep learning solutions at scale.
Key job responsibilities
- Analyze the data and metrics resulting from traffic into Amazon's product search service.
- Design, build, and deploy effective and innovative ML solutions to improve search.
- Evaluate the proposed solutions via offline benchmark tests as well as online A/B tests in production.
- Publish and present your work at internal and external scientific venues in the fields of ML/NLP/IR.
- 4+ years of applied research experience
- 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 with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Experience with building search and recommendation systems
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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 Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit
https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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.
