Research Manager

Meta Meta · Big Tech · Burlingame, CA

Research Manager at Meta focused on product-focused signal processing and sensor development for novel wearable devices and algorithms. The role involves leading a team of research scientists and engineers to create practical, non-invasive wearable devices using machine learning and statistical signal processing to understand user intent and action. Responsibilities include managing teams, collaborating with cross-functional groups (hardware, ML research/engineering), developing methodologies for signal simulation, improving ML models based on sensor limitations, and fostering a learning environment.

What you'd actually do

  1. Lead a team of research scientists and research engineers to deliver high-quality products and solutions
  2. Manage career guidance for the team through regular feedback and tracking performance
  3. Collaborate with cross functional teams including hardware, machine learning research and engineering teams to develop scalable systems to characterize sensor performance and their impact on product features
  4. Develop scalable methodologies and tools to simulate biophysical signals and their approximations
  5. Explore methods to improve ML models for product features by incorporating knowledge of sensor performance limitations

Skills

Required

  • Signal processing
  • Sensor development
  • Machine learning
  • Statistical signal processing
  • Team management
  • Cross-functional collaboration
  • Human-in-loop sensor/wearable biosensor development
  • Consumer hardware experience

Nice to have

  • Ph.D. in machine learning, AI, computer science, electrical engineering, statistics, applied mathematics, data science, signal processing, optimization or related technical fields
  • Experience defining research/technical direction for a team
  • Experience with biosensors (EKG/ECG, PPG, capacitive sensing, electromyography)

What the JD emphasized

  • product-focused
  • wearable devices
  • algorithms
  • machine learning
  • statistical signal processing
  • neuromotor signals
  • sensor performance
  • product features
  • ML models
  • sensor performance limitations
  • product development targets
  • human-in-loop sensor/wearable biosensor development
  • consumer hardware space

Other signals

  • machine learning
  • wearable devices
  • sensor development
  • algorithms
  • neuromotor signals