Meta AI Systems team is seeking strong Postdoctoral Researcher candidates to work on applied research on training efficiency, scalability, stability for large scale Deep Neural Networks (DNN), with a focus on content ranking and recommendation systems (RecSys). Our team supports the research and development of a wide range of Artificial Intelligence and Machine Learning techniques. It provides internal platforms and tools to train and deploy some of the most advanced machine learning models for all Meta products. A Postdoctoral Researcher at AI Systems typically works as an applied researcher and engineer, solving some of the most challenging and interesting problems in the training process of large, complex DNN models. The specific research area may include: 1. The application of Graph Learning in recommendation systems. 2. Performance optimization for large scale sequential models in content ranking. 3. Parameter Efficiency Fine Tuning of large language models and transformer models. 4. General improvement of the training process of DNNs, in terms of efficiency and reliability. For this position, the applicant will engage with the supervisor and other researchers, engineers to implement research agenda, publish world-class research works, and make impacts on some key Meta products. You will be able to gain valuable experience in an industry-leading organization, solving real-world problems, and advance SotA.