Robotic Controls Researcher

Meta Meta · Big Tech · Redmond, WA

Robotic Controls Researcher at Meta Reality Lab Research focusing on developing control algorithms for robotics platforms, including model predictive control and generative AI models. The role involves data collection and evaluation for training autonomous control policy models, with a strong emphasis on research contributions and publications in top conferences.

What you'd actually do

  1. Conducting collaborative research on developing control algorithms for a wide range of robotics platforms
  2. Development of model predictive control approaches mapping robot observations and target references to low-level actuation control signals
  3. Development of robotic data collection sets and evaluations

Skills

Required

  • Ph.D. in Mechanical Engineering, Electrical Engineering, Control Systems Engineering, Computer Science, or relevant degree and 5+ years experience in robotic control systems
  • 5+ years experience with both traditional reflexive controllers (PID, LQR, OSC) and modern predictive controllers (MPCs)
  • Experience with generative AI models such as transformers, LLMs, VLMs, VLAs, and diffusion models
  • Track record of research contributions published in top conferences and journals
  • Experience with robotic data collection for training autonomous control policy models
  • Experience with physical systems, including interfacing with novel sensors and actuators
  • Experience working with robot manipulation

Nice to have

  • Bachelor's degree in Mechanical Engineering, Electrical Engineering, Control Systems Engineering, Computer Science, or in a relevant technical field, or equivalent practical experience

What the JD emphasized

  • Ph.D. in Mechanical Engineering, Electrical Engineering, Control Systems Engineering, Computer Science, or relevant degree and 5+ years experience in robotic control systems
  • 5+ years experience with both traditional reflexive controllers (PID, LQR, OSC) and modern predictive controllers (MPCs)
  • Experience with generative AI models such as transformers, LLMs, VLMs, VLAs, and diffusion models
  • A track record of research contributions with your work published in top conferences and journals such as Robotics (RSS, ICRA, IROS, CoRL, T-RO, IJRR), Machine Learning (NeurIPS, ICML, ICLR, AAAI, JMLR), and Computer Vision (CVPR, ICCV, ECCV, TPAMI)
  • Experience with robotic data collection for training autonomous control policy models

Other signals

  • robot embodiments
  • modern control policies
  • robotic dexterous manipulation
  • generative AI models
  • robotic data collection
  • autonomous control policy models
  • robot manipulation