Research Engineer, Monetization AI

About the Role

The Monetization Ranking and Foundational AI organization is dedicated to delivering personalized ads that maximize both user utility and advertiser value. This role focuses on advancing AI, ML, and RecSys technologies for all aspects of Monetization, including ranking, retrieval, model architecture, and optimization. By integrating cutting-edge AI/ML/RecSys advancements, the team helps Meta’s products achieve long-term goals and has contributed tens of billions in revenue. The team is seeking AI/ML/RecSys specialists to drive SOTA research and production.

Key Responsibilities

• Develop and implement large-scale model architectures, leveraging model scaling and transfer learning techniques.
• Prioritize training scalability and signal scaling to optimize model performance, efficiency, and reliability.
• Develop and apply NextGen sequence learning techniques to drive advancements in recommender systems and machine learning.
• Design and implement generative modeling solutions for data augmentation.
• Develop and deploy machine learning pipelines.
• Collaborate with cross-functional teams to design and optimize ML systems, leveraging expertise in hardware-software co-design, including quantization, compression, and resource-efficient AI.
• Develop and implement innovative solutions for data-related challenges, utilizing knowledge of semi/self-supervised learning, generative techniques, sampling, debiasing, domain adaptation, continual learning, data augmentation, cold-start, content understanding, and large language models.

Requirements & Tech Stack

• Minimum Qualifications:
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• Research experience in machine learning, deep learning, natural language processing, and/or recommender systems.
• Experience with developing machine learning models at scale from inception to business impact.
• Programming experience in Python and hands-on experience with frameworks such as PyTorch.
• Exposure to architectural patterns of large scale software applications.
• Preferred Qualifications:
• PhD in AI, Computer Science, Data Science, or related technical fields.
• Master's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• First author publications at peer-reviewed AI conferences (e.g., NeurIPS, ICML, ICLR, ICCV, CVPR, ACL, EMNLP, RecSys, KDD, WSDM, TheWebConf, ICDM, AAAI).
• Direct experience in generative AI, LLMs, RecSys, ML research.
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements).
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews).
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies.

About Meta

Meta builds technologies that help people connect, find communities, and grow businesses.

Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable.

In addition to base compensation, Meta offers benefits.