Research Engineer, Monetization AI 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 natural language processing and understanding
• Design and implement generative modeling solutions for data augmentation
• Research and develop graph-aware large language models
• Develop and deploy AutoML pipelines
• Apply Reinforcement Learning (RL) techniques, including long-term value optimization, RLHF, and RL4Reason
• Use causal learning to identify and understand the cause and effect of relationships across data
• 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, to drive performance improvements and efficiency gains
• 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

Minimum Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 2+ years of experience holding an industry, faculty, or government researcher or applied researcher position, or related position
• Research experience in deep learning, reinforcement learning, natural language processing, computer vision, recommendations, ranking, search, or related areas
• Programming experience in Python and hands-on experience with frameworks such as PyTorch
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

Preferred Qualifications:

• Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward.
• Experience working and communicating cross functionally in a team environment.
• First author publications at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, ACL).
• Master's degree or PhD in Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, or relevant technical field.
• Experience taking ideas from research to production.
• 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: