Robotics Engineer, Technical Lead

Applied Intuition Applied Intuition · Robotics · Sunnyvale, CA · Engineering Leadership

Founding technical role to build and shape Applied Intuition's robotics organization. Define technical direction, write production code, and build functional demos on physical hardware. Focus on software and learned behaviors, with engagement across the hardware stack. Responsibilities include defining architecture, writing production code (Python/C++), training/evaluating/deploying learning-based policies for manipulation and locomotion, building hardware demos, establishing simulation infrastructure, analyzing telemetry, and working with data pipelines to close the sim-to-real gap.

What you'd actually do

  1. Define and own the technical architecture for humanoid robotics software, spanning perception, planning, control, and learned behaviors
  2. Write production-quality code in Python and C++ and ship it to physical robots — this is a hands-on individual contributor role first
  3. Design, train, evaluate, and deploy learning-based policies for manipulation and locomotion
  4. Build functional demonstrations on multiple robot hardware platforms that prove out capabilities and inform the product roadmap
  5. Establish simulation infrastructure and validate behaviors in physics-based environments before deploying to hardware

Skills

Required

  • BS, MS, or PhD in Robotics, Computer Science, Electrical Engineering, or a related field, or equivalent hands-on experience
  • 7+ years of experience in robotics software development, with a meaningful portion on physical humanoid, legged, or highly dexterous manipulation platforms
  • Strong proficiency in Python and C++ for robotics and ML systems; experience with PyTorch or equivalent deep learning frameworks
  • Deep understanding of robotics fundamentals: kinematics, dynamics, control theory, state estimation, and perception
  • Experience building and evaluating visuomotor or multimodal policies end to end, from data collection through deployment
  • Ability to operate independently in an early-stage environment, make architectural decisions with limited information, and build from scratch

Nice to have

  • Experience with state-of-the-art bi-dexterous mobile hardware platforms, including dexterous manipulation and whole body control
  • Familiarity with hardware bring-up, sensor integration, or embedded systems; ability to engage with mechanical and electrical teams at a subsystem level
  • Background in SLAM, 3D perception, or sensor fusion (IMU, lidar, cameras, force/torque)
  • Experience with physics simulators such as MuJoCo, NVIDIA Isaac Sim, or Gazebo
  • Familiarity with ROS/ROS2 or similar robotics middleware
  • Publication record or open-source contributions in robot learning, embodied AI, or manipulation

What the JD emphasized

  • Proven track record shipping learning-based systems — behavior cloning, RL, or VLA policies — to real robots in production or near-production settings
  • Comfort on the lab floor — debugging physical robots, running hardware-in-the-loop tests, and iterating on live systems

Other signals

  • Define and own the technical architecture for humanoid robotics software, spanning perception, planning, control, and learned behaviors
  • Design, train, evaluate, and deploy learning-based policies for manipulation and locomotion
  • Build functional demonstrations on multiple robot hardware platforms that prove out capabilities and inform the product roadmap
  • Establish simulation infrastructure and validate behaviors in physics-based environments before deploying to hardware
  • Work with teleoperation and data collection pipelines to generate training data and close the sim-to-real gap