- 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.
