Research Scientist, Contextual AI and Multimodal Agents

Meta is seeking a Research Scientist to advance foundational machine learning research that powers products used by billions of people worldwide. In this role, you will identify and solve the hardest open problems in core ML — spanning areas such as multimodal learning, foundation models, large-scale model training, efficient inference, and agentic systems — and translate breakthrough research into systems that fundamentally improve Meta's products and platforms.

This is a senior individual-contributor role for a recognized technical authority. You will define the long-term technical vision for your research area, serve as a principal driver of Meta's most ambitious bets in machine learning, and align work across disciplines and organizations around a coherent multi-year direction. You will remain technically deep—prototyping critical-path ideas, stress-testing results, and making consequential technical decisions—while multiplying the impact of other researchers and engineers through mentorship, collaboration, and clear scientific judgment.

Research Scientist, Contextual AI and Multimodal Agents Responsibilities:

Define and drive a multi-year research strategy for core machine learning, connecting areas such as multimodal understanding, foundation models, efficient training and inference, and agentic reasoning into a coherent research portfolio

Serve as a principal technical driver for critical, high-risk research bets with multi-year potential, carrying them from problem formulation through scientific validation, system demonstration, and productization

Lead ambitious research initiatives across algorithm and system design, implementation, experimentation, evaluation, and transfer into reusable platforms or product capabilities

Develop novel ML algorithms and architectures—including training, post-training, reinforcement-learning, and evaluation methods—that advance the state of the art in areas such as large-scale optimization, representation learning, and generalization

Advance efficient training and inference through model compression, quantization, distillation, adaptive computation, and hardware-software co-design for on-device and large-scale deployment

Establish shared datasets, benchmarks, evaluation frameworks, and research platforms that raise the quality bar across multiple teams and product areas

Identify new product opportunities and build durable collaborations across Meta, academia, and industry to move research into widely useful technology

Mentor researchers and engineers across teams, provide technical counsel on consequential decisions, and raise the scientific and engineering bar for the broader organization

Publish influential research, contribute open-source software and datasets where appropriate, and strengthen Meta's position in the research community through talks, collaborations, and service

Partner with legal, policy, and compliance teams to ensure that ML research and deployment practices uphold privacy, security, and responsible AI standards

Minimum Qualifications:

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Engineering, Electrical Engineering, or a related technical field
12+ years of research or applied-development experience in machine learning, artificial intelligence, or related areas

Recognized authority in a relevant research area, with demonstrated breadth across adjacent areas such as multimodal learning, foundation models, efficient AI systems, or agentic AI Experience setting the technical direction for a research area and leading multiple complex initiatives whose methods, systems, or strategy were…