Research Engineer role focused on building Meta's User Intelligence Engine for the Recommendation System, integrating Generative AI/LLMs with ranking expertise to deliver personalized experiences. Responsibilities include developing large-scale model architectures, leveraging transfer learning, optimizing training scalability, applying sequence learning, designing generative modeling for data augmentation, and deploying ML pipelines. Requires a Bachelor's degree in a relevant field, ML/deep learning/recommender systems experience, Python/PyTorch proficiency, and exposure to large-scale software patterns. Preferred qualifications include a Master's/PhD, publication record, generative AI/LLM/RecSys experience, and experience with large-scale ML model development.

Research Engineer focused on advancing AI, ML, and RecSys technologies for personalized ads, aiming to maximize user utility and advertiser value. The role involves developing and implementing large-scale model architectures, sequence learning techniques, and generative modeling solutions for data augmentation, with a focus on integrating these into production systems that drive significant revenue.