Applied Scientist, AWS Marketplace & Partner Services
Seattle, Washington, USA
Amazon.com
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The AWS Marketplace & Partner Services Science team is hiring an Applied Scientist to develop science products that support AWS initiatives to grow AWS Partners. The team is seeking candidates with strong background in machine learning and engineering, creativity, curiosity, and great business judgment. As an applied scientist on the team, you will work on targeting and lead prioritization related AI/ML products, recommendation systems, and deliver them into the production ecosystem. You are comfortable with ambiguity and have a deep understanding of ML algorithms and an analytical mindset. You are capable of summarizing complex data and models through clear visual and written explanations. You thrive in a collaborative environment and are passionate about learning.
Key job responsibilities
- Work with scientists, product managers and engineers to deliver high-quality science products
- Experiment with large amounts of data to deliver the best possible science solutions
- Design, build, and deploy innovative ML solutions to impact AWS Co-Sell initiatives
About the team
The AWS Marketplace & Partner Services team is the center of Analytics, Insights, and Science supporting the AWS Specialist Partner Organization on its mission to provide customers with an outstanding experience while working with AWS partners. The Science team supports science models and recommendation systems that are deployed directly to AWS Customers, AWS partners, and internal AWS Sellers.
- PhD, or Master's degree and 4+ years of building machine learning models for business application experience
- Experience with data querying languages (e.g., SQL)
- Deep knowledge of natural language processing, deep learning, and recommendation systems
- Experience programming in Java, Python or related language
- Experience deploying recommendation models into production systems
- Experience leveraging large language models (LLMs) and developing production generative AI applications
- Knowledge of architectural concepts and parallel and distributed computing
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.
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 $136,000/year in our lowest geographic market up to $222,200/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.
Key job responsibilities
- Work with scientists, product managers and engineers to deliver high-quality science products
- Experiment with large amounts of data to deliver the best possible science solutions
- Design, build, and deploy innovative ML solutions to impact AWS Co-Sell initiatives
About the team
The AWS Marketplace & Partner Services team is the center of Analytics, Insights, and Science supporting the AWS Specialist Partner Organization on its mission to provide customers with an outstanding experience while working with AWS partners. The Science team supports science models and recommendation systems that are deployed directly to AWS Customers, AWS partners, and internal AWS Sellers.
Basic Qualifications
- PhD, or Master's degree and 4+ years of building machine learning models for business application experience
- Experience with data querying languages (e.g., SQL)
- Deep knowledge of natural language processing, deep learning, and recommendation systems
- Experience programming in Java, Python or related language
Preferred Qualifications
- Experience in professional software development- Experience deploying recommendation models into production systems
- Experience leveraging large language models (LLMs) and developing production generative AI applications
- Knowledge of architectural concepts and parallel and distributed computing
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.
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 $136,000/year in our lowest geographic market up to $222,200/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.
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Category:
Data Science Jobs
Tags: AWS Deep Learning Engineering Generative AI Java LLMs Machine Learning ML models NLP PhD Python SQL
Perks/benefits: Career development Equity / stock options
Region:
North America
Country:
United States
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