Senior Machine Learning Engineer - Ads Retrieval
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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 senior 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
Drive technical roadmaps and lead day to day project execution, and contribute meaningfully to team vision and strategy
Work on large scale data systems, backend services and product integration
Collaborate closely with multiple stakeholders cross product, engineering, research and marketing
Be a mentor and cross-functional advocate for the team
Who You Might Be:
2+ years of experience with leading applied machine learning models with Tensorflow/Pytorch with large-scale ML systems
5+ 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:
Comprehensive Healthcare Benefits
401k Matching
Workspace benefits for your home office
Personal & Professional development funds
Family Planning Support
Flexible Vacation (please use them!) & Reddit Global Wellness Days
4+ months paid Parental Leave
Paid Volunteer time off
