Figure AI
State Estimation Engineer, Data Collection Systems
$150K–$300K
San Jose, CA +1 · Full-time · Posted Aug 18, 2026
- Location
- San Jose, CA
San Jose, California, United States - Experience
- 4+ years.
About the job
Design and deploy state-estimation and calibration systems that enable real-time humanoid teleoperation and precise offline motion reconstruction for data collection and policy training.
What you'll do
- Develop real-time filtering and offline batch optimization pipelines for state estimation.
- Create user calibration workflows and sensor-fusion methods for full-body kinematic tracking.
- Build validation and diagnostic tools, assess sensing limitations, and inform future hardware design.
What they ask for
- 4+ years of experience building multi-sensor fusion and state-estimation solutions for dynamic hardware systems.
- Expertise in real-time filtering and offline batch optimization tools.
- Experience designing calibration, zeroing, and alignment workflows for multi-sensor suites and kinematic models.
- Strong foundation in 3D kinematics and constrained optimization, with high-performance C++ and Python skills.
Nice to have
- Experience with low-latency teleoperation, haptics, or human-in-the-loop control systems; background in human biomechanics, skeletal tracking, or body-mounted telemetry.
- Experience applying Machine Learning (ML) to motion priors, trajectory smoothing, or learned state estimation/calibration.
Pay
$150,000 to $300,000 per year (base salary)
Tools
C++, Python, (E)KFs, sliding-window estimators, Factor Graphs, GTSAM, Ceres, Non-Linear Least Squares
AI focus
Develop state-estimation systems for humanoid motion data collection and policy training; preferred experience includes applying Machine Learning to motion priors, trajectory smoothing, or learned state estimation/calibration.
Model-written summary · the original posting is authoritative