AppLovin is looking to advance recommender systems by creating new recommendation models and paradigms, leveraging rich live user data and large-scale compute to validate models rapidly, and publishing findings to contribute to the broader ML and RecSys community.
Requirements
- PhD (or equivalent research experience) in CS, ML, Statistics, or related field.
- Strong background in deep learning.
- Proven track record of research excellence (publications, awards, impactful projects).
- Proficiency in Python and modern ML frameworks (PyTorch).
- Experience with large-scale data and experimentation.
- Publications in top venues (NeurIPS, ICML, ICLR, KDD, RecSys, SIGIR, WWW).
- Experience with sequential modeling, representation learning, or causal inference.
Responsibilities
- Drive foundational research to create new recommendation models and paradigms.
- Leverage rich live user data and large-scale compute to validate models rapidly.
- Collaborate closely with engineering and product teams to operationalize research.
- Publish findings and contribute to the broader ML and RecSys community.
Other
- We’re looking for rising researchers with strong academic backgrounds and a desire to have real-world impact.
- AppLovin provides a competitive total compensation package with a pay for performance rewards approach.
- Total compensation at AppLovin is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience.
- AppLovin is proud to be an equal opportunity employer that is committed to inclusion and diversity.
- If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send us a request at accommodations@applovin.com.
