Staff Machine Learning Engineer, Ads Prediction
As a company, Reddit primarily generates revenue through advertising, and we're working towards building a massive business to fund our mission. We distinguish ourselves from other digital ad platforms by attracting advertisers who want to connect with a specific target audience because of our passionate and engaged communities.
Ads prediction team is responsible of predicting ads engagement rates used in auctions to maximize ad engagements and marketplace efficiency. This team owns a critical piece in the ads delivery pipeline and Machine Learning infrastructure. Project highlights:
Model architecture engineering via exploring different state-of-the-art model architectures such as Multi-task learning, Attention Layer
Systematic feature engineering to build power features from Reddit’s data with aggregation, embedding, sub-models, content understanding techniques, etc.
Build efficient ML infrastructure and tools such as auto ML flows and batch feature engineering framework, to accelerate ML dev cycle
As a Staff Machine Learning Engineer in the Ads prediction team, you will serve as a visionary in researching, formulating, and executing projects. You will actively participate in the end-to-end implementation process, and collaborate with cross-functional teams to ensure successful product delivery. You will be responsible for the quality and technical approach within the team; partner with other leads in direction setting, planning, and overseeing eng designs and executions; establish and contribute to the group’s culture and processes.
Your Responsibilities:
Building industrial-level models for critical ML tasks with advanced modeling techniques
Research, implement, test, and launch new model architectures including deep neural networks with advanced pooling and feature interaction architectures
Systematic feature engineering works to convert all kinds of raw data in Reddit (dense & sparse, behavior & content, etc) into features with various FE technologies such as aggregation, embedding, sub-models, etc.
Be a mentor and cross-functional advocate for the team
Drive the formulation and execution of team strategy.
Who You Might Be:
Tracking records of consistently driving KPI wins through systematic works around model architecture and feature engineering
5+ years of experience with industry-level deep learning models
5+ years of experience with mainstream ML frameworks (such as Tensorflow and Pytorch)
6+ years of end-to-end experience of training, evaluating, testing, and deploying industry-level models
6+ years of experience of orchestrating complicated data generation pipelines on large-scale dataset
Experience with Ads domain is a plus
Experience with recommendation system 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