State Estimation Engineer, Data Collection Systems

Job summary

Responsibilities

We are looking for a State Estimation Engineer to own the architecture, algorithm development, and calibration workflows for a next-generation data collection system. This system powers two core capabilities: low-latency real-time teleoperation of our humanoid robots and ultra-high-precision…

• Design and implement dual-tier state estimation algorithms in modern C++: low-latency, real-time filters for streaming teleoperation and batch optimization/smoothing routines for…
• Own and develop subject-calibration procedures, designing rapid, intuitive routines to estimate individual body segment dimensions, joint offsets, and sensor-to-body extrinsics…
• Develop robust sensor fusion architectures combining spatial transforms, visual-inertial data, and inertial signals into full-body kinematic pose estimates.
• Address spatiotemporal sensor calibration, dynamic environmental interference, and kinematic constraint enforcement on human skeletal models.
• Develop techniques to extract useful information from compliant tactile sensing in the presence of large sensor deformation, stretching or folding.

What they're looking for

• 4+ years of experience building multi-sensor fusion and state estimation solutions for dynamic hardware systems.
• Hands-on expertise with both real-time filtering techniques ((E)KFs, sliding-window estimators) and offline batch optimization tools (Factor Graphs, GTSAM, Ceres, Non-Linear…
• Proven capability to design fast, reliable calibration, zeroing, and alignment workflows for multi-sensor suites and kinematic models.
• Deep mathematical foundation in 3D spatial kinematics, Lie groups (SE(3), SO(3)), forward/inverse kinematics, and constrained optimization.
• Proven ability to write high-performance, modular C++ for embedded or edge computing platforms alongside Python for data analysis and visualization.

Tech stack

• C++
• Python