AI Research Scientist, Visual Coding - MSL FAIR

We are seeking AI research scientists to help us build Meta's most advanced multimodal large language models. To push the frontier of what those models can generate, we need to work with data and train at scale, and advance our visual coding capabilities.

Our team contributes across all stages of development (pre-training, mid-training, post-training) and all multimodal modalities (image, video, audio, 3D). We are tackling complex challenges at trillion-scale, including organic data curation, synthetic data generation, agent and interaction data, visual code generation, agent post-training, and frontier paradigms that redefine what is possible.

Based in Meta Superintelligence Labs (MSL) within the Fundamental AI Research Organization (FAIR), you will directly contribute to Meta's frontier models and collaborate with scientists and engineers across MSL.

Responsibilities

Apply specialized expertise in visual code generation for 3D, web, and game environments
Execute on high-priority projects in pre-training, mid-training, or post-training data curation and evaluation development
Collaborate with cross-functional teams to develop Meta’s next foundational models
Lead complex technical projects end-to-end

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience
A PhD in Computer Science or a related technical field
2+ years of industry research experience with large language or large media models, computer vision, or related AI/ML models
Experience as a formal technical lead, leading major technical initiatives with cross-functional impact, and/or influencing strategy across multiple teams
Experience in visual code generation - generating code that produces visual output for 3D, web, or game environments
Experience with multimodal pre-training or mid-training data curation for large media perception models
Published research in leading peer-reviewed conferences (e.g., ACL, NeurIPS, ICML, ICLR, AAAI, KDD, CVPR, ICCV) and/or demonstrated significant industry influence in the field of AI Experience working on frontier-quality and state-of-the-art Large Language or Large Media Models
Programming experience in Python and hands-on experience with frameworks like PyTorch or Spark, or related distributed computing frameworks (Ray, DataFlow)
Familiarity with SQL and file formats, such as Hive, Iceberg, Parquet, etc
First-author publications in leading peer-reviewed conferences (e.g., ACL, NeurIPS, ICML, ICLR, AAAI, KDD, CVPR, ICCV)