Confirmed on the employer's own hiring board on Oct 25, 2026. First seen by Alion on Oct 14, 2026. Meta scores B on the Alion truth index.
Responsibilities
Define and drive the research strategy and roadmap for an AI research team focused on wearables, EMG, and wearable sensors, balancing applied machine learning investments with product deliverables Lead the development of novel AI architectures, training methodologies, and evaluation frameworks for EMG signal processing, sensor fusion, and wearable device intelligence Establish technical direction for the team by identifying high-impact research problems in sensor signal interpretation and wearable AI, scoping projects, and aligning efforts to broader organizational priorities Build and grow a high-performing team of AI researchers and engineers through hiring, mentorship, and structured development of research talent Collaborate with product, engineering, and hardware partners to translate research breakthroughs in EMG and sensing into production wearable systems at Meta's scale Drive promising research outcomes from research to production, ensuring innovative findings are successfully transitioned into scalable wearable products and features Communicate research findings and strategic recommendations to organizational leaders and cross-functional stakeholders through written reports, presentations, and design reviews Foster a team culture that values scientific rigor, engineering craft, and responsible AI development in alignment with Meta's values and compliance standards
Qualifications
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 12+ years of experience in AI or machine learning research, including experience leading research teams or large-scale research programs Experience establishing research strategy and roadmaps with demonstrated impact on AI systems or products at scale Experience attracting, developing, and retaining research talent, including building leadership pipelines through internal development and external hiring Track record of executing cross-functional AI research initiatives from ideation through deployment, including managing dependencies across engineering, product, and data science teams Experience communicating complex AI research directions and technical decisions to both technical and non-technical audiences through written and verbal formats Experience publishing AI, machine learning, or biosignal processing research in peer-reviewed venues such as NeurIPS, ICML, ICLR, IEEE EMBC, or similar venues Experience leading research in one or more specialized domains, such as EMG signal processing, wearable computing, health sensors, human-computer interaction, or physiological signal analysis

