Real-Time State Estimation Engineer - Data Fusion

Figure-

San Jose (CA)

On-site

USD 150,000 - 300,000

Full time

3 days ago

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Job summary

Figure- in San Jose, CA is seeking a State Estimation Engineer to own architecture, algorithm development, and calibration workflows for a next-generation data collection system powering real-time teleoperation and offline trajectory reconstruction. You will build dual-tier estimation pipelines, fusion of heterogeneous sensors, and calibration routines.

The role requires 4+ years of multi-sensor experience, strong math background, and proficiency in C++ and Python.

Qualifications

4+ years of experience building multi-sensor fusion and state estimation for dynamic hardware.
Hands-on with real-time filtering techniques (EKF/UKF) and offline batch optimization tools (GTSAM, Ceres).
Design fast, reliable calibration and alignment workflows for multi-sensor suites.
Strong foundation in 3D spatial kinematics, SE(3)/SO(3) and constrained optimization.
Proficient in C++ for embedded/edge computing and Python for data analysis.

Responsibilities

Design and implement dual-tier state estimation algorithms for real-time and offline use.
Develop calibration procedures for body segments and sensor-to-body extrinsics.
Create sensor fusion architectures with visual-inertial data for full-body pose.
Address calibration and kinematic constraints on skeletal models.
Explore new sensing modalities to inform hardware design.
Build validation pipelines and error analysis for online/offline algorithms.
Diagnose hardware limitations and guide future design.
Own diagnostic tooling for data collection pipelines.