Meta is seeking a Research Scientist manager to lead teams advancing AI capabilities for wearables and health applications. In this role, you will manage research & engineering teams working on machine learning solutions for wearable devices, health monitoring, biometric sensing, and wellness-focused AI systems. You will shape the research strategy for AI-powered health and wearables experiences, guide the translation of novel findings into impactful product features, and partner closely with hardware, applied research, engineering, and product organizations to deliver meaningful health and wellness outcomes at scale.

Qualifications:

8+ years of experience in machine learning research or applied machine learning, with depth in areas such as LLM mid/post-training, applied AI, wearable computing, or on-device machine learning 4+ years of experience managing research or engineering teams, including experience managing other research leaders or technical leads Experience driving research strategy and roadmap decisions across the full ML research lifecycle, from problem formulation and experimentation through publication and production impact Experience partnering cross-functionally with hardware, engineering, product, and data science teams to translate ML research into measurable outcomes for consumer devices Experience recruiting, developing, and retaining research scientists and building high-performing research teams Experience with on-device ML optimization, including model compression, efficient inference, and power-aware deployment for resource-constrained hardware Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Experience managing teams working on applications of large language models in consumer tech Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Track record of publishing impactful research at top ML venues such as NeurIPS, ICML, ICLR, CHIL, or equivalents, and guiding teams to do the same Experience adhering to and implementing responsible and ethical AI practices for health applications, including privacy protection, bias mitigation, and clinical validation considerations