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Apptronik is a human-centered robotics company developing AI-powered humanoid robots (Apollo) to support humanity across manufacturing, logistics, healthcare, and beyond. As a Senior Perception Hardware Engineer, you will own the critical sensor calibration systems that enable Apollo's autonomy stack to perceive and interact with the physical world.
You will design and implement the complete calibration architecture for Apollo's multi-modal perception suite, including intrinsic models for optical sensors (pinhole, fisheye, Brown-Conrady, Kannala-Brandt distortion models) and inertial measurement units (IMU bias, scale factors, random walk). You will develop highly accurate extrinsic calibration methods for sensor-to-sensor and sensor-to-kinematic-base spatial transformations, ensuring sub-microsecond temporal synchronization across all perception streams using Precision Time Protocol (PTP), pulse-per-second (PPS), and hardware triggering.
On the hardware side, you will design precision calibration fixtures and targets (CharuCo boards, custom 3D geometries) and optimize lighting environments for high-repeatability factory calibration. You will collaborate with mechanical engineers to evaluate sensor mounting rigidity and characterize calibration drift caused by thermal gradients, mechanical shock, and joint wear.
You will build the automated end-of-line (EOL) calibration pipeline for manufacturing, enabling non-engineers to reliably calibrate Apollo's multi-sensor head in minutes. You will also develop lightweight online and in-field auto-calibration routines that allow Apollo to detect sensor drift and dynamically adjust extrinsic transforms without human intervention. Finally, you will establish a data-tracking architecture to monitor fleet-wide calibration health and identify batch variances or hardware degradation over time.
This role requires 5+ years of industry experience in perception hardware, computer vision, or robotics with a primary focus on sensor calibration and validation. You must have deep expertise in 3D geometry, linear algebra, coordinate frame transformations (quaternions, rotation matrices, SE(3)), and non-linear optimization (least-squares, bundle adjustment). Strong programming skills in Python and C++ are essential, along with extensive experience using computer vision libraries (OpenCV, PCL) and optimization frameworks (Ceres Solver, g2o). You need hands-on experience with optical components, LiDAR mechanisms, and MEMS IMUs, understanding the physical limitations causing optical distortion, rolling shutter artifacts, and IMU drift. An MS or PhD in Robotics, Electrical Engineering, Optical Engineering, Computer Science, or related field is required.
