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 for 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 powerful 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 machine learning engineer in the Ads prediction team, you will research, formulate, and execute projects, and actively participate in the end-to-end implementation process. You will collaborate with cross-functional teams to ensure successful product delivery. You will also be able to contribute your expertise and shape the future of ads ML at Reddit.

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.  
• Contribute meaningfully to team strategy. We give everyone a seat at the table and encourage active participation in planning for the future

Who You Might Be:

• Tracking records of consistently driving KPI wins through systematic works around model architecture and feature engineering
• 3+ years of experience with industry-level Machine Learning models
• 3+ years of experience with mainstream ML frameworks (such as Tensorflow and Pytorch)
• 3+ years of end-to-end experience of training, evaluating, testing, and deploying industry-level models
• Deep learning experience is a strong plus
• Experience in orchestrating complicated data generation pipelines on large-scale dataset is a plus
• Experience with Ads domain is a plus
• Experience with Recommendation Systems 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