Machine Learning Engineer, App Ads

We’re evolving and continuing our mission to bring community belonging and empowerment to everyone in the world. Providing a delightful and relevant experience to our users applies to our Ads like all of our offerings and we’re excited to build a product that is best-in-class for our users and advertisers. The year ahead is a busy one - join us!

The App Ads Team is entrusted with the development and maintenance of a diverse set of Machine Learning models that are responsible for predictions regarding user conversions after engaging with Reddit. The creation and enhancement of these models plays a crucial role in our organization's efforts to optimize advertising effectiveness and drive business growth. We are looking for a motivated engineer that will help us advance our vision. As a diverse group of software engineers product managers data scientists and ads experts we are excited for you to join our team!

Your Responsibilities :

• Develop advanced and scalable deep learning models using cutting-edge techniques for critical machine learning tasks within the app conversions modeling domain.

• Design and implement innovative strategies for signal loss mitigation ensuring the accuracy and reliability of predictions in the presence of incomplete or noisy data.

• 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.

• 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:

• 2+ years of experience with industry-level deep learning models.

  • 2+ 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.

  • 3+ years of experience of orchestrating complicated data generation pipelines on large-scale datasets.

  • Experience with ads domain and conversion modeling 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