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Kalman Filter Estimation Jobs in Texas (NOW HIRING)

Shield AI

Senior Manager, Perception (R3634)

Dallas, TX

$229K - $343K/yr

Working knowledge of Kalman Filter, Factor Graphs and other modern estimator fundamentals. * Strong working knowledge of Computer Vision with hands-on experience with OpenCV or similar CV libraries.

Shield AI

Senior Manager, Perception (R3634)

Dallas, TX ยท On-site

$96K - $121K/yr

Working knowledge of Kalman Filter, Factor Graphs and other modern estimator fundamentals. * Strong working knowledge of Computer Vision with hands-on experience with OpenCV or similar CV libraries.

AI Chopping Block

Senior Manager, GNC (R5627)

Dallas, TX ยท On-site

$140 - $200/hr

... theState Estimation team, the Simulation Development team, the Aerodynamicsteam and ... Filter development and verification / validation * Discrete filters * Kalman filters * C++ and ...

Shield AI

Senior Manager, GNC (R5627)

Dallas, TX ยท On-site

$230K - $350K/yr

... State Estimation team, the Simulation Development team, the Aerodynamics team and the Embedded ... Filter development and verification / validation * Discrete filters * Kalman filters * C++ and ...

Shield AI

Senior Manager, GNC (R5627)

Dallas, TX

$230K - $350K/yr

... State Estimation team, the Simulation Development team, the Aerodynamics team and the Embedded ... Filter development and verification / validation * Discrete filters * Kalman filters * C++ and ...

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Kalman Filter Estimation information

What is Kalman filter estimation?

Kalman Filter Estimation is a mathematical algorithm used to estimate the state of a dynamic system from a series of noisy measurements. It is widely applied in fields such as robotics, aerospace, and navigation to provide real-time, optimal estimates of unknown variables by combining predictions from a model with observed data. The filter works recursively, meaning it updates its estimates and uncertainties as new measurements become available. Its strength lies in efficiently handling uncertainties and noise in both the system model and the measurements.

What are the key skills and qualifications needed to thrive as a Kalman filter estimation engineer, and why are they important?

To excel as a Kalman Filter Estimation Engineer, you need a strong background in control theory, linear algebra, statistics, and typically a degree in electrical engineering, robotics, or applied mathematics. Familiarity with MATLAB, Python, C++, and simulation tools like Simulink, as well as experience implementing Kalman filters in real-time systems, is highly valued. Analytical thinking, problem-solving, and effective communication are important soft skills for collaborating with multidisciplinary teams and presenting complex results. These competencies ensure accurate state estimation and system reliability in applications such as navigation, robotics, and sensor fusion.

What are some common challenges faced by professionals working in Kalman filter estimation, and how can they be addressed?

Professionals working in Kalman Filter Estimation often encounter challenges such as model inaccuracies, noisy sensor data, and computational limitations, especially in real-time applications. Addressing these issues typically involves rigorous sensor calibration, careful tuning of filter parameters, and choosing appropriate variants of the Kalman filter, such as the Extended or Unscented Kalman Filter for nonlinear systems. Collaboration with domain experts and regular validation against ground truth data also help ensure robust performance. Additionally, staying updated with the latest research and tools in estimation theory can provide innovative solutions to emerging challenges.

What is the difference between Kalman Filter Estimation vs Signal Processing Engineer?

AspectKalman Filter EstimationSignal Processing Engineer
CredentialsMathematics, control systems, engineering degreesElectrical engineering, computer science, or related fields
Work EnvironmentResearch labs, aerospace, robotics, automationCommunications, audio/video, telecommunications industries
Industry UsageNavigation, robotics, sensor fusionFiltering, data analysis, signal enhancement

Kalman Filter Estimation focuses on estimating the state of dynamic systems using mathematical models, often in robotics and navigation. Signal Processing Engineers design and implement algorithms to analyze and modify signals in various industries. While both roles involve data analysis and mathematical skills, Kalman Filter Estimation is specialized in state estimation for control systems, whereas Signal Processing Engineers work broadly on signal manipulation and enhancement.

What are popular job titles related to Kalman Filter Estimation jobs in Texas?

For Kalman Filter Estimation jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Kalman Filter Estimation jobs in Texas look for?

The top searched job categories for Kalman Filter Estimation jobs in Texas are:

What cities in Texas are hiring for Kalman Filter Estimation jobs?

Cities in Texas with the most Kalman Filter Estimation job openings:

Kalman Filter Estimation jobs near you
Infographic showing various Kalman Filter Estimation job openings in Texas as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Principal Engineer, State Estimation (R4602)

Shield AI

Dallas, TX

$270K - $400K/yr

Full-time

Re-posted 2 days ago

Job description

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BATย aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visitย www.shield.ai. Follow Shield AI onย LinkedIn,ย X,ย Instagram, andย YouTube.ย 

Job Description:
We are looking for an experienced state estimation engineer to design, develop, and support the deployment of safety-critical navigation solutions for aerospace platforms. This role requires deep expertise in state estimation theory, extensive practical experience implementing ownship navigation systems in the aerospace domain, and strong software development skills for production-quality navigation code. The engineer will design and implement a unified navigation architecture that supports traditional GNSS/IMU fusion while being extensible to all-source navigation strategies incorporating diverse sensing modalities for GPS-degraded and denied environments.
What you'll do:
Navigation System Architecture & Design:
  • Establish navigation performance requirements and error budgets for safety-critical applicationsย 
  • Support decomposition of navigation requirements into allocations for sensors, estimation algorithms, and software componentsย 
  • Design detailed software architecture for state estimation implementations, including module interfaces and data flowย 
Algorithm Development & Implementation:
  • Design and implement Extended Kalman Filter algorithms for navigation applications, with broad understanding of state estimation theory and alternative filtering approachesย 
  • Implement tightly-coupled and loosely-coupled GNSS/INS integration algorithmsย 
  • Integrate diverse sensing modalities (vision, RF, celestial etc.) into multi-sensor fusion framework for GPS-degraded environmentsย 
  • Develop fault detection, isolation, and recovery (FDIR) strategies for navigation systemsย 
  • Implement integrity monitoring and protection level calculations for safety-critical operationsย 
Certification & Verification:
  • Develop verification and validation test plans for navigation algorithmsย 
  • onduct performance analysis including Monte Carlo simulation, covariance analysis, and flight test data evaluationย 
  • Document navigation system design, requirements allocation, and compliance evidenceย 
  • Support safety assessment activities including failure modes and effects analysisย 
Technical Leadership:
  • Provide technical guidance on navigation architecture and state estimation approachesย 
  • Support trade studies evaluating navigation sensor suites and fusion strategiesย 
  • Mentor junior engineers on state estimation theory and implementationย 
Required qualifications:
  • MS or PhD in Computer Science, Software Engineering, Electrical Engineering, Aerospace Engineering, Mechanical Engineering, Applied Mathematics, or related fieldย 
    15+ years of experience developing state estimation algorithms for aerospace navigation applicationsย 
  • Demonstrated experience implementing GNSS/INS integration solutionsย 
  • Experience with safety-critical system development and certification processesย 
  • Deep understanding of state estimation theoryย 
  • Experience implementing multi-sensor fusion algorithms in production systemsย 
  • Strong background in inertial navigation, GNSS positioning, and sensor error modelingย 
  • Strong programming skills in C/C++ and Python/MATLAB for algorithm development and analysisย 
  • Understanding of integrity monitoring, protection levels, and safety assessment methodsย 
  • Experience with requirements management and verification/validation processes for certifiable systemsย 
  • Understanding of GPS/GNSS signal structure, error sources, and performance characteristicsย 
  • Knowledge of IMU error models, calibration, and Allan variance analysisย 
  • Familiarity with alternative navigation sensors (camera, RF ranging, celestial, etc.)ย 
  • Understanding of navigation performance metrics (accuracy, integrity, continuity, availability)
  • Must be eligible to obtain a clearance
  • Ability to obtain a S//SAR level security clearance desired.
Preferred qualifications:
  • PhD in relevant field with focus on state estimation or navigationย 
  • Direct involvement in certified navigation system development from requirements through flight testย 
  • Experience with specialized navigation approaches (vision-aided navigation, terrain-referenced navigation, celestial navigation, etc.)ย 
  • Publications or patents in navigation or state estimationย 
  • Experience with GPS/GNSS jamming and spoofing mitigation techniquesย 
$270,000 - $400,000 a year
#LI-SM1
#LF

Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
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Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
ย 
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed toย equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.ย 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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