drjobs Applied Scientist, NAS Mosaic

Applied Scientist, NAS Mosaic

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1 Vacancy
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Job Location drjobs

Seattle - USA

Yearly Salary drjobs

$ 136000 - 223400

Vacancy

1 Vacancy

Job Description

Are you passionate about solving unique customer-facing problem in the Amazon scale Are you excited by developing and productizing machine learning deep learning algorithms and leverage tons of Amazon data to learn and infer customer shopping patterns Do you enjoy working with a diversity of engineers machine learning scientists product managers and user-experience designers If so you have found the right match!

Fashion is extremely fast-moving visual subjective and it presents numerous unique problem domains such as product recommendations product discovery and evaluation. The vision for Amazon Fashion is to make Amazon the number one online shopping destination for Fashion customers by providing large selections inspiring and accurate recommendations and customer experience.

The mission of Size/Fit science team as part of Fashion Tech is to innovate and develop scalable ML solutions to provide personalized size and fit recommendations when Amazon Fashion customers evaluate apparels or shoes online. The team is hiring an experienced Applied Scientist who has a solid background in applied Machine Learning including computer vision recommendation systems and generative AI.

Key job responsibilities
Key job responsibilities
- You will work on our Science team and partner closely with other scientists data engineers as well as product managers UX designers and business partners to answer complex problems with novel scientific approaches.
- You can navigate ambiguous problems by working backward from customer needs to propose and develop effective scientific solutions.
- You have excellent communication skills to be able to work with cross-functional team members to understand key questions and earn the trust of senior leaders.
- You are able to multi-task between different tasks such as gap analysis of algorithm results integrating multiple disparate datasets doing business intelligence analyzing engagement metrics or presenting to stakeholders.
- You thrive in an agile and fast-paced environment on highly visible projects and initiatives.

- 3 years of building models for business application experience
- PhD or Masters degree and 4 years of CS CE ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java C Python or related language
- Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing high-performance computing

- Experience using Unix/Linux
- Experience in professional software development

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

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 for more information. If the country/region youre applying in isnt 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 $136000/year in our lowest geographic market up to $223400/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.

Employment Type

Full-Time

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