Staff Research Engineer, MetaAI Assistant Measurement

Meta Superintelligence Labs is seeking a Staff Research Engineer to provide technical leadership for the team working on the next generation of AI Assistants powered by frontier-scale foundation models. This is a high-impact Individual Contributor (IC) role focused on architecting cutting-edge measurement and evaluation paradigms that align fast-moving model development with real end-user value.As a Staff Research Engineer, you will define the scientific "North Star" behind the evaluation flywheel, drive technical success across methodologies, and partner with product, engineering, and model training teams to steer the system toward reliability and trustworthiness at scale. You will act as a technical anchor, influencing the roadmap through scientific rigor and hands-on contribution.

Staff Research Engineer, MetaAI Assistant Measurement Responsibilities:

• Architect Scientific Strategy: Define and lead the execution of the scientific roadmap for AI Assistant measurement, ensuring methodologies are rigorous, scalable, and aligned with product goals
• Innovate & Build: Spearhead the research and development of novel offline and online evaluation metrics, automated benchmarks, and synthetic data generation pipelines to close the loop between model training and deployment
• Cross-Functional Technical Leadership: Serve as the primary scientific liaison to pre-training, post-training, and product teams, ensuring that measurement insights directly influence model architecture and training recipes (the "evaluation flywheel")
• Mentorship & Influence: Provide technical mentorship and guidance to senior research engineers and applied scientists, fostering a culture of scientific rigor and code without direct management responsibilities
• Hands-on Contribution: Remain hands-on in code and research, building prototypes for new evaluation frameworks and validating novel measurement theories

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Track record of driving technical strategy and landing large-scale research or product impacts in a time-sensitive environment
• Proven technical vision regarding the future trajectory of Generative AI, specifically in how model performance translates to user utility
• Expertise in designing and implementing online and offline measurement systems, benchmark building, and data synthesis techniques
• Experience leading complex, cross-functional technical initiatives, driving consensus across engineering, research, and product boundaries
• Proficiency in Python and deep learning frameworks (e.g., PyTorch), with the ability to prototype and implement complex methodologies

• PhD in Machine Learning, Statistics, Econometrics, Causal Inference, Computer Science, or related fields
• 8+ years of experience, or PhD + 6 years of hands-on experience in large language models, NLP, and Transformer modeling, within both research and engineering development settings
• Significant experience developing comprehensive evaluation frameworks for LLMs, multimodal models, or agentic systems
• Expertise in online measurement, user-behavior modeling, counterfactual analysis, and A/B testing platform design
• Demonstrated background in AI system benchmarking, Reward modeling, RL, content evaluation, or human-AI interaction
• Track record of publication in top-tier conferences (NeurIPS, ICLR, ICML, ACL) or significant contributions to open-source AI ecosystems
• Ability to communicate complex scientific concepts clearly to executive leadership and non-technical stakeholders to influence high-level decision-making
• Experience building and curating large-scale datasets and ontologies used for training or evaluation