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Applied Scientist II, Vertical Search Relevance
Amazon
On-sitemidPosted June 2, 2026
About the Role
Build and deploy machine learning models for product search, develop new ranking features and techniques, and own the full development cycle including A/B testing and production deployment.
Requirements
Requires expertise in machine learning, ability to build and deploy ML models for product search, develop new ranking features, and own the full development cycle from design to A/B testing and production deployment.
Full Job Description
The Amazon Search team creates strong 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 a strong applied scientists to join the Vertical Search Relevance India team. This team’s 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.
Key job responsibilities
Key job responsibilities
* Build machine learning models for Product Search.
* Develop new ranking features and techniques building upon the latest results from the academic research community.
* Propose and validate hypothesis to direct our business and product road map. Work with engineers to make low latency model predictions and scale the throughput of the system.
* Focus on identifying and solving customer problems with simple and elegant solutions.
* Design, develop, and implement production level code that serves billions of search requests. Own the full development cycle: design, development, impact assessment, A/B testing (including interpretation of results) and production deployment.
* Collaborate with other engineers and related teams within A9.com and Amazon.com to find technical solutions to complex design problems.
* Take ownership. Understand the needs of various search teams, distill those into coherent projects, and implement them with an eye on long-term impact.
* Be a leader. Use your expertise to set a high bar for the team, mentor team members, set the tone for how to take on and deliver on large impossible-sounding projects.
* Be ambitious. Find and eagerly tackle hard problems.
* Be curious. You will work alongside systems engineers, machine learning scientists, and data analysts. Your effectiveness and impact will depend on discussing problems with and learning from them. You will have access to the latest technologies and vast technical tools and resources of Amazon and will need to learn how to use them effectively.
* Be customer focused. Work backwards from customer problems, figure out elegant solutions, and implement them for speed and scalability.
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 a strong applied scientists to join the Vertical Search Relevance India team. This team’s 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.
Key job responsibilities
Key job responsibilities
* Build machine learning models for Product Search.
* Develop new ranking features and techniques building upon the latest results from the academic research community.
* Propose and validate hypothesis to direct our business and product road map. Work with engineers to make low latency model predictions and scale the throughput of the system.
* Focus on identifying and solving customer problems with simple and elegant solutions.
* Design, develop, and implement production level code that serves billions of search requests. Own the full development cycle: design, development, impact assessment, A/B testing (including interpretation of results) and production deployment.
* Collaborate with other engineers and related teams within A9.com and Amazon.com to find technical solutions to complex design problems.
* Take ownership. Understand the needs of various search teams, distill those into coherent projects, and implement them with an eye on long-term impact.
* Be a leader. Use your expertise to set a high bar for the team, mentor team members, set the tone for how to take on and deliver on large impossible-sounding projects.
* Be ambitious. Find and eagerly tackle hard problems.
* Be curious. You will work alongside systems engineers, machine learning scientists, and data analysts. Your effectiveness and impact will depend on discussing problems with and learning from them. You will have access to the latest technologies and vast technical tools and resources of Amazon and will need to learn how to use them effectively.
* Be customer focused. Work backwards from customer problems, figure out elegant solutions, and implement them for speed and scalability.