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Ads Retrieval team’s mission is to identify the business opportunities, provide ML models and data driven solutions on candidate sourcing, recommendation, early ranking and filtering in Ads upper funnel. The team works on:
Build and iterate on candidate sourcing and early ranking Machine Learning models and algorithms to find the most relevant, engaging and diversified ads candidates for global optimization and various product use cases. Design and establish a large scale candidate indexing system to enable efficient candidate retrieval at a scale of millions to billions, which powers ads recommendation and ranking with good balance between quality and computation efficiency.
As a machine learning engineer in the ads retrieval team, you will research, formulate and execute on our mission to build end-to-end ML solutions and deliver the right ad to the right user under the right context with data and ML driven solutions.
Your Responsibilities:
Building ads retrieval and early ranking system for critical ML tasks with advanced industrial level techniques Research, implement, test, and launch new model architectures including information retrieval, ANN, recommendation system, deep neural networks within high dimensional information system Work on large scale data systems, backend services and product integration Collaborate closely with multiple stakeholders cross product, engineering, research and marketing
Who You Might Be:
+ years of experience with applied machine learning models with Tensorflow/Pytorch with large-scale ML systems + years of end-to-end experience of training, evaluating, testing, and deploying machine learning models Proficiency with programming languages (Java, Python, Golang, C++, or similar) and statistical analysis. Experience of orchestrating complicated data pipelines and system engineering on large-scale dataset Prior experience with information retrieval and recommendation system Ads domain knowledge on product and ML solutions is a plus
Benefits:
Pension Scheme Private Medical and Dental Scheme Life Assurance, Income Protection Workspace benefit for your home office Personal & Professional development funds Family Planning Support Commuter Benefits Flexible Vacation & Reddit Global Days Off
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