Research Engineer - Robot Learning

Applied Intuition Applied Intuition · Robotics · Sunnyvale, CA · AI Research

Research Engineer role focused on robot learning, including setting up hardware, constructing simulation environments for RL training, processing human data for robotics, and collaborating on research publications and end-to-end algorithm deployment for autonomous systems. The role involves working with foundation models, diffusion policies, multi-modal robot learning, VLA post-training, and reinforcement learning.

What you'd actually do

  1. Support the team robotic and data collection hardware set up, and design the mechatronic system for customized demands
  2. Construct robotic simulation environments at scale and use it for RL training
  3. Process human data for robotic use cases
  4. Work closely with Research Scientists and interns on high-quality research publications to submit to top-tier conferences
  5. Collaborate with our engineering teams on ADAS, data, and simulation to deploy end-to-end algorithms for mass production vehicles, and neural simulation/generation for tools supporting autonomy development

Skills

Required

  • Python
  • Pytorch
  • computer vision
  • robotics systems
  • distributed machine learning model training
  • World-action foundation model
  • video/Gaussian generation
  • diffusion policy
  • multi-modal robot learning
  • VLA post-training
  • reinforcement learning
  • Physics-aware reconstruction
  • deformable simulation

Nice to have

  • Industry experience on relevant topics (self-driving application preferred)
  • MSc or PhD in machine learning and computer vision with autonomy and robotics applications or closely related field
  • Passion for building and shipping customer-focused software frameworks or tools

What the JD emphasized

  • high-quality research publications
  • end-to-end algorithms for mass production vehicles

Other signals

  • robot learning
  • RL training
  • autonomous driving
  • humanoid robots