Applied Scientist SCOT RL
Applied Scientist SCOT RL
Posted on :
07-04-2025
Employer Active
1 Vacancy
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Yearly Salary
$ 136000 - 223400
Vacancy
1 Vacancy
Posted on :
07-04-2025
Job Description
Our team is at the forefront of machine learning research. Led by scientists including Dean Foster the team is dedicated to developing innovative RL algorithms and applying them to complex realworld challenges in Amazons global inventory and supply chain network. Our focus is not just on advancing theoretical knowledge but also on implementing these insights to optimize operations and enhance customer satisfaction.
We foster a collaborative environment where exploration of new ideas and tackling complex problems is encouraged. The supply chain spans a wide range of operationsmanaging decisions that impact billions of dollars worth of inventory. For scientists passionate about impactful research in machine learning and AI our team offers a dynamic and fulfilling environment to make a tangible difference in the field and Amazons operations.
Key job responsibilities
* Design implement and evaluate innovative models agents and software prototypes.
* Collaborate with a team of experienced scientists to drive technological advancements.
* Develop innovative solutions to complex business problems in collaboration with partner teams.
* Contribute to Amazons global science community through collaboration and publication of groundbreaking research.
* Engage in research projects that contribute to the wider scientific community sharing findings through publications in toptier journals and conferences.
A day in the life
As a part of our team you will be working alongside thought leaders like Dean Foster contributing to academic research and complex realworld applications. Your work will directly influence Amazons global inventory planning systems shaping decisions that affect billions of dollars worth of inventory and a wide array of product lines.
You will tackle complex inventory planning challenges using Reinforcement Learning contributing both to the theoretical aspect of the field and its practical applications. We value innovative thinking and the ability to approach problems from new perspectives.
PhD or Masters degree and 4 years of CS CE ML or related field experience
Experience programming in Java C Python or related language
Experience in building machine learning models for business application
1 years of practical machine learning experience
1 years of handson predictive modeling and large data analysis experience
Experience in professional software development
Experience in stateoftheart deep learning models architecture design and deep learning training and optimization and model pruning
Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs GANs VAEs and NF
Experience in patents or publications at toptier peerreviewed conferences or journals
Experience with PyTorch
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 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 jobrelated knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity signon 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.
We foster a collaborative environment where exploration of new ideas and tackling complex problems is encouraged. The supply chain spans a wide range of operationsmanaging decisions that impact billions of dollars worth of inventory. For scientists passionate about impactful research in machine learning and AI our team offers a dynamic and fulfilling environment to make a tangible difference in the field and Amazons operations.
Key job responsibilities
* Design implement and evaluate innovative models agents and software prototypes.
* Collaborate with a team of experienced scientists to drive technological advancements.
* Develop innovative solutions to complex business problems in collaboration with partner teams.
* Contribute to Amazons global science community through collaboration and publication of groundbreaking research.
* Engage in research projects that contribute to the wider scientific community sharing findings through publications in toptier journals and conferences.
A day in the life
As a part of our team you will be working alongside thought leaders like Dean Foster contributing to academic research and complex realworld applications. Your work will directly influence Amazons global inventory planning systems shaping decisions that affect billions of dollars worth of inventory and a wide array of product lines.
You will tackle complex inventory planning challenges using Reinforcement Learning contributing both to the theoretical aspect of the field and its practical applications. We value innovative thinking and the ability to approach problems from new perspectives.
PhD or Masters degree and 4 years of CS CE ML or related field experience
Experience programming in Java C Python or related language
Experience in building machine learning models for business application
1 years of practical machine learning experience
1 years of handson predictive modeling and large data analysis experience
Experience in professional software development
Experience in stateoftheart deep learning models architecture design and deep learning training and optimization and model pruning
Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs GANs VAEs and NF
Experience in patents or publications at toptier peerreviewed conferences or journals
Experience with PyTorch
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 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 jobrelated knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity signon 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
Key Skills
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