Jobs / United States / Figure AI INC
State Estimation Engineer, Data Collection Systems
Figure AI INC · 🇺🇸 San Jose, CA
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 22 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 1 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Figure AI INC paid sponsored hires in similar roles1 certified filing for “AI ENGINEER, DATA INFRASTRUCTURE” (Database Architects) in CA: $300k–$300k, median $300k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
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Sponsor Radar — Figure AI INC
The US Department of Labor certified 22 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 1 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Figure AI INC →
About the role
Figure is an AI robotics company developing autonomous general-purpose humanoid robots. The goal of the company is to ship humanoid robots with human level intelligence. Its robots are engineered to perform a variety of tasks in the home and commercial markets. Figure is headquartered in San Jose, CA. 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 offline trajectory reconstruction for data collection and policy training. You will build and deploy dual-tier estimation pipelines and user-onboarding calibration routines that fuse heterogeneous sensor modalities to track full-body human kinematics and floating-base motion across dynamic tasks. Responsibilities: • 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 high-accuracy offline dataset generation. • Own and develop subject-calibration procedures, designing rapid, intuitive routines to estimate individual body segment dimensions, joint offsets, and sensor-to-body extrinsics whenever a user equips the system. • 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. • Diagnose and understand limitations of existing hardware or designs and inform future design requirements. • Evaluate novel sensing modalities to inform future hardware designs. • Build diagnostic tooling, validation pipelines, and error analysis workflows to evaluate accuracy for both online and offline algorithms. Requirements: • 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 Least Squares). • 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. Bonus Qualifications: • Experience with low-latency streaming pipelines for teleoperation, haptics, or human-in-the-loop control systems. • Background in human biomechanics, skeletal tracking, or body-mounted telemetry systems. • Prior experience applying Machine Learning (ML) techniques to motion priors, trajectory smoothing, or learned state estimation/calibration. The US base salary range for this full-time position is $150,000 to $300,000 per year. The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.