Job Description

Job Description

In the Amazon Selection Monitoring team, we have the goal of establishing the most comprehensive, accurate and fresh universal selection of products. We enrich and increase the quality and coverage of Amazon product selection using the advanced machine learning and big data technologies.

We are looking for highly motivated scientists who can lead the design, development, deployment and maintenance of data-driven models using machine learning (ML) and/or natural language (NL) and computer vision (CV) applications. Your models would be monitoring billions and billions of products. You will build Amazon scale applications running on Amazon Web Service (AWS) that both leverage and create new technologies to process large volumes of data that derive patterns and conclusions from the data.

Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.

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Responsibilities

Designing and implementing new features and machine learned models, including the application of state-of-art deep learning to solve search matching and ranking problems, including filtering, new content indexing, and apply document understanding
Conducting and coordinating process development leading to improved and streamlined processes for model development. Strong customer focus is essential
Working closely with Product Managers to expand depth of our product insights with data, create a variety of experiments, and determine the highest-impact projects to include in planning roadmaps
Providing technical and scientific guidance to your team members
Communicating effectively with senior management as well as with colleagues from science, engineering, and business backgrounds
Being a cultural leader that ensures teams are collecting, understanding, and using data to inform every decision that impacts our customers

The successful candidate will have an established background in developing customer-facing experiences, a strong technical ability, a start-up mentality, excellent project management skills, and great communication skills.
BASIC QUALIFICATIONS- 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
PREFERRED QUALIFICATIONS- 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.

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

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