Applied Scientist II, Vertical Search
Applied Scientist II, Vertical Search
Posted on :
26-05-2025
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1 Vacancy
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Job Description
The Amazon Search team creates customer-focused search and advertising 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.
Amazon has grown rapidly and will continue to do so in foreseeable future. Providing a high quality search experience is a unique challenge as Amazon expands to new customers countries categories and product lines. We are seeking applied scientists to join the newly formed Relevance India team. This teams charter is to increase the pace at which Amazon expands and improve the search experience at launch. In practice we aim to invent universally applicable signals and algorithms for training machine-learned ranking models and improve the machine-learning framework for training and offline evaluation that is used for all new relevance models.
- 3 years of building models for business application experience
- 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
- Masters degree or above in computer science machine learning engineering or related fields
- PhD in computer science computer engineering or related field
- Experience with large scale distributed systems such as Hadoop Spark etc.
- fundamentals on a broad set of ML approaches and techniques
- fundamentals in problem solving and algorithm design.
- interest in learning researching and creating new technologies with commercial impact
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.
Amazon has grown rapidly and will continue to do so in foreseeable future. Providing a high quality search experience is a unique challenge as Amazon expands to new customers countries categories and product lines. We are seeking applied scientists to join the newly formed Relevance India team. This teams charter is to increase the pace at which Amazon expands and improve the search experience at launch. In practice we aim to invent universally applicable signals and algorithms for training machine-learned ranking models and improve the machine-learning framework for training and offline evaluation that is used for all new relevance models.
- 3 years of building models for business application experience
- 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
- Masters degree or above in computer science machine learning engineering or related fields
- PhD in computer science computer engineering or related field
- Experience with large scale distributed systems such as Hadoop Spark etc.
- fundamentals on a broad set of ML approaches and techniques
- fundamentals in problem solving and algorithm design.
- interest in learning researching and creating new technologies with commercial impact
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.
Employment Type
Full-Time
Key Skills
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