ADCI
Technology
AppliedScientistII,VerticalSearchRelevance
Neural analysis suggests this role is
optimal for Mid candidates.
“Applied Scientist II, Vertical Search Relevance at ADCI. Skills: Machine learning, Search relevance, Ranking models. Build machine learning models. Develop ranking features”
Industry & Context.
Problem solving; Algorithm design
What They're Looking For.
Must Have
3+ years building models, Master's degree, Experience programming Java, Experience programming C++, Experience programming Python, Experience algorithms data structures, Experience parsing, Experience numerical optimization, Experience data mining, Experience parallel distributed computing, Experience high-performance computing
Nice to Have
PhD, Experience large scale distributed systems, ML approaches and techniques fundamentals, Problem solving fundamentals, Algorithm design fundamentals, Interest in learning new technologies, Interest in researching new technologies, Interest in creating new technologies
What You'll Do.
Build machine learning models
Develop ranking features
Develop ranking techniques
Make low latency model predictions
Scale system throughput
Identify customer problems
Solve customer problems
Design production level code
Develop production level code
Implement production level code
Own development cycle
Interpret A/B test results
Collaborate with engineers
Find technical solutions
Understand search team needs
Distill needs into projects
Set high bar for team
Work with systems engineers
Work with machine learning scientists
Work with data analysts
Learn new technologies
Use technical resources
Work backwards from customer problems
Figure out elegant solutions
Implement solutions for speed
Implement solutions for scalability
How You'll Work.
Team & Collaboration
Related teams within A9.com; Amazon.com teams
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 co
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