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Meta

Research Scientist, AI (Technical Leadership)

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What they do

A Research Scientist is responsible for designing, undertaking and analyzing information from controlled laboratory-based investigations, experiments and trials.

$157,644 / year median in California

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Job Description

Meta is seeking a Research Scientist to lead AI research initiatives at the intersection of wearable technology and AI modeling of diverse sensors including EMG, health sensors, audio, and video. In this role, you will define and drive the research agenda for a team of AI researchers, computational neuroscientists, and engineers, shaping the direction of next-generation AI capabilities that power Meta's wearable devices and health-focused experiences. You will operate at the frontier of AI research for human-computer interaction, translating scientific advances in biosignal interpretation into scalable systems with measurable product impact.
Qualifications:
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 building AI research organizations from early-stage through scaled operations, including defining team structure and operating models 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 Experience publishing AI, machine learning, or biosignal processing research in peer-reviewed venues such as Neur
IPS, ICML, ICLR, IEEE
EMBC, or similar