Sensor Calibration Engineer

At Mentee Robotics, we are redefining humanoid automation with an AI-first approach - combining perception, reasoning, and dexterous manipulation into fully autonomous systems that continuously learn and improve. We offer an exceptional opportunity to participate in building next-generation commercial humanoid robots from 0 to 1, alongside competitive compensation, and an international engineering environment. We are expanding with a new robotics Engineering Center in China, working hand-in-hand with our engineering teams in headquarters. Its mission: to rapidly develop our next-generation full-size humanoid platform and bring it to production.

We are looking for a Sensor Calibration Engineer to own intrinsic and extrinsic calibration algorithms, online self-recalibration routines, software calibration pipelines, and spatial-temporal alignment for our humanoid robot’s multi-modal sensor suite (cameras, LiDAR, IMU, kinematics, and force-torque sensors).

Who you are:

• Calibration specialist deeply versed in 3D geometry, spatial transformations, state estimation, non-linear optimization, and sensor error modeling.
• Hands-on engineer who excels at mathematical model formulation, algorithmic solver design, and numerical optimization.
• Driven to translate complex calibration formulations into automated software routines and online self-correcting algorithms.
• A strong collaborator across computer vision, SLAM, state estimation, control, and production quality teams.

Responsibilities:

• Design and implement intrinsic and extrinsic calibration algorithms for multi-camera systems, LiDAR, IMU, joint encoders, and force/torque sensors.
• Develop joint spatial-temporal calibration pipelines to accurately estimate inter-sensor rotation/translation matrices and temporal offsets.
• Architect automated calibration software pipelines and trajectory generation algorithms to support scalable sensor calibration workflows.
• Implement online self-calibration and drift-tracking algorithms to maintain cross-sensor spatial alignment during continuous dynamic motion.
• Integrate kinematic-visual-inertial calibration algorithms to model structural compliance, thermal expansion, and gravity deflection.
• Deliver calibrated transformations (TF trees, extrinsic matrices, distortion parameters) directly into perception, localization, and control stacks.
• Conduct residual error sensitivity analysis, repeatability validation, and environmental robustness testing across thermal cycles and dynamic vibration.

Requirements:

• B.Sc. or M.Sc. in Computer Science, Robotics, or related technical disciplines.
• 3+ years of hands-on experience in multi-sensor calibration, computer vision geometry, spatial optimization, or SLAM/state estimation.
• Solid mathematical foundation in 3D rigid-body transformations, Lie algebra (SE(3), SO(3)), non-linear optimization (Ceres, g2o), and Kalman filtering.
• Proficient in Modern C++ and Python, with experience utilizing OpenCV, PCL, and ROS 2 coordinate transformation tools (TF2).
• Practical experience in camera intrinsic/extrinsic calibration, camera-LiDAR calibration, and camera-IMU spatiotemporal calibration (e.g., Kalibr).
• Experience developing automated calibration software workflows and verification tools.
• Strong analytical problem-solving skills and rigorous data-driven evaluation methodologies.

Advantages:

• Direct experience in humanoid or quadruped kinematic-visual-inertial self-calibration routines.
• Knowledge of thermal error modeling for IMU gyroscopes/accelerometers and optical sensor distortion.
• Comfortable communicating technical topics in English with international teams.