AI Research Scientist, Visual Coding - MSL FAIR

Summary:

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.

Required Skills:

AI Research Scientist, Visual Coding - MSL FAIR Responsibilities:

1. Apply specialized expertise in visual code generation for 3D, web, and game environments

2. Execute on high-priority projects in pre-training, mid-training, or post-training data curation and evaluation development

3. Collaborate with cross-functional teams to develop Meta’s next foundational models

4. Lead complex technical projects end-to-end

Minimum Qualifications:

Minimum Qualifications:

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

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

3. A PhD in Computer Science or a related technical field

4. 2+ years of industry research experience with large language or large media models, computer vision, or related AI/ML models

5. Experience as a formal technical lead, leading major technical initiatives with cross-functional impact, and/or influencing strategy across multiple teams

6. Experience in visual code generation - generating code that produces visual output for 3D, web, or game environments

7. Experience with multimodal pre-training or mid-training data curation for large media perception models

8. 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

Preferred Qualifications:

Preferred Qualifications:

1. Experience working on frontier-quality and state-of-the-art Large Language or Large Media Models

2. Programming experience in Python and hands-on experience with frameworks like PyTorch or Spark, or related distributed computing frameworks (Ray, DataFlow)

3. Familiarity with SQL and file formats, such as Hive, Iceberg, Parquet, etc

4. First-author publications in leading peer-reviewed conferences (e.g., ACL, NeurIPS, ICML, ICLR, AAAI, KDD, CVPR, ICCV)

Public Compensation:

$184,000/year to $257,000/year + bonus + equity + benefits

Industry: Internet

Equal Opportunity:

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [email protected].