Research Engineer, Pre-training Data - MSL FAIR

Meta • Menlo Park, CA

2h

About The Position

Meta is seeking AI research engineers to help build the data foundation for Meta's most advanced Large Language Models. The role involves working with data at scale and pushing beyond the data ceiling. The team contributes to data curation across all stages of LLM development (pre-training, mid-training, post-training) and all domains/modalities (e.g., web, code, agent, multilingual). They tackle challenges at trillion-scale, including organic data curation, synthetic data generation, agent and interaction data, and frontier paradigms. Based in Meta Superintelligence Labs (MSL) within the Fundamental AI Research Organization (FAIR), the role directly contributes to Meta’s frontier models like Llama, with opportunities to collaborate with researchers and engineers across MSL.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 2+ years of industry research experience in LLM/NLP 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
• Practical experience with pre-training or mid-training data curation for large foundational models and experience working with organic, synthetic, agentic, or reasoning data for LLMs
• Demonstrated data infrastructure and software background, and experience building data tooling and services
• Published research in leading peer-reviewed conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP) and/or demonstrated significant industry influence in the field of AI
• Experience working on frontier-quality/state-of-the-art Large Language Models

Nice To Haves

• Masters degree or PhD in Computer Science or a related technical field
• Hands-on experience with modeling frameworks like PyTorch
• Hands-on experience on SQL and large-scale data handling, with familiarity of frameworks like Spark and Hive

Responsibilities

• Collaborate with cross-functional teams to develop Meta’s next foundational models
• Architect efficient and scalable data curation systems and pipelines
• Fundamentally improve our data velocity across workflows and projects by contributing to the advancement of data tooling
• Execute on high priority projects in pre-training, mid-training, or post-training data curation
• Apply specialized expertise in agentic data, synthetic data, reasoning data, web parser, coding data, data scaling laws, or datamix optimization
• Lead complex technical projects end-to-end

What This Job Offers

• Job Type: Full-time
• Career Level: Senior