State Estimation and Navigation Engineer

New York Technology Partners; Seattle (WA); On-site; USD 120,000 - 170,000; Full time

Job summary

New York Technology Partners seeks a senior estimator architect to lead the design and implementation of navigation and estimation systems for flight-critical platforms. You will define estimator architectures, fuse multi-sensor data, and ensure validation across simulations and live flight data.

You will collaborate with guidance and control teams, address GNSS-denied navigation, and optimize performance under low-SWaP constraints. Travel for flight tests is required.

Qualifications

• Hands-on Kalman-class estimators with EKF/UKF applied to real systems.
• Experience with estimation for mobile/field robotics in real-world conditions.
• Proven track record validating estimators on hardware using flight or experimental data.
• Strong C++ on-vehicle and Python for analysis and simulation.
• Willingness to travel for flight tests.

Responsibilities

• Lead design and implementation of the navigation and estimation stack.
• Collaborate with guidance and controls teams on estimator architecture and validation.
• Develop solutions for GNSS-denied navigation and sensor fusion in real time.
• Ensure robustness to latency, sensor degradation, and multi-sensor fusion.
• Validate estimators across SITL/HITL and real flight data.

Skills

C++

Python

Kalman estimators

Estimation theory

Robotics

Travel readiness

Education

MS in Aerospace Engineering / related field

Tools

GTSAM

CERES

ROS/ROS2

VIO

Job description

You will lead the design and implementation of the navigation and estimation stack, from first-principles observability analysis through flight-proven embedded execution. You will work in close partnership with the guidance and controls teams, but the architecture, rigor, and validation of the estimation solution are yours to drive.

You will focus on problems in all of the following areas:

• Estimator Architecture & Design: Select and justify the estimator architecture the problem actually demands, including KF variants, factor graphs, and related approaches, grounded in observability analysis of the vehicle dynamics and sensor suite rather than defaulting to a familiar filter.
• State-Driven Guidance & Control Co-Design: Work across the estimation-G&C boundary to align the available state with the guidance and control laws the intercept requires, recognizing that estimator capability and achievable guidance are mutually constraining.
• GPS-Contested & Denied Navigation: Develop navigation solutions that hold up as GNSS degrades or disappears, maintaining a trustworthy state through the regimes where a bad estimate ends the mission.
• Multimodal Sensor Fusion: Fuse heterogeneous sensing, including inertial, GNSS, vision, and seeker/target sensors, into a coherent, real-time state under low-SWaP constraints.
• Robustness to Latency & Degradation: Handle delayed and asynchronous measurements, detect and ride through sensor degradation or outright failure, and inform the case for redundant or complementary sensing where the estimate demands it.
• Target-Relative Navigation: Estimate the relative state of maneuvering targets with the fidelity and latency the intercept demands.
• Sensor Selection & Integration: Partner with the hardware and electrical design teams to drive sensor selection, placement, and integration, closing the loop between what the estimator needs and what the vehicle carries.
• Flight Validation: Prove estimators against truth data across SITL/HITL and real flight; instrument, troubleshoot, and characterize filter behavior from telemetry and logs.

Basic Qualifications

• Education: MS in Aerospace Engineering, Electrical Engineering, Mechanical Engineering, Robotics, Computer Science, or a related field, ideally with a concentration in estimation, navigation, or sensor fusion.
• Estimation Depth: Hands-on expertise with Kalman-class estimators, including EKF/UKF, and the underlying theory, including process and measurement modeling, observability, tuning, and consistency analysis, applied to real systems rather than textbook problems.
• Mobile or Field Robotics Estimation Experience: Direct experience developing state estimation for mobile or field robotics platforms, including ground, aerial, legged, or marine systems, operating in real-world conditions with onboard sensing and motion.
• Real-System Validation: A track record of taking estimators beyond simulation onto hardware and validating them against flight or experimental truth data.
• Software Skills: Strong C++ for on-vehicle implementation and Python for analysis and simulation.
• Travel: Ability to travel as necessary to support rigorous flight testing events and campaigns.

Preferred Qualifications

Experience in any of the following areas is a plus:

• Education: PhD in a relevant field with a research focus in estimation, navigation, or sensor fusion.
• GPS-Contested & Denied Navigation: Direct experience maintaining a trustworthy state as GNSS degrades or disappears, including alternative navigation, integrity monitoring, or anti-jam/anti-spoof awareness.
• Target Tracking: Relative-state estimation against maneuvering targets, including high-G or high-closing-rate engagements.
• Advanced Estimation Methods: Factor graphs, fixed-lag smoothing, GTSAM/Ceres or equivalent, and visual-inertial odometry (VIO).
• Embedded & Real-Time Deployment: Estimators running on resource-constrained targets, including STM32, Jetson, and FPGA platforms, under RTOS/Linux, with attention to timing, fixed-point/numerical issues, and high-rate telemetry.
• Simulation & Validation: High-fidelity physics modeling and digital-twin replication for estimator development and SITL/HITL validation.
• Flight Regimes: High-speed multirotor or rocket systems; nonlinear dynamics and transition maneuvers.
• Software Frameworks: ROS/ROS2 or other custom, lightweight middlewares.