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Kalman Filtering Inertial Navigation Jobs in Texas

L3HHCM20

Specialist, GNC Engineer

Richardson, TX · On-site

Responsibilities include developing and evaluating guidance, navigation, and control algorithms ... Familiarity with a variety of tracker types and Kalman filtering. * Background in physics/rigid ...

Apptronik

Sr. Software Engineer - Wheeled Controls

Austin, TX · On-site

$44.75 - $57.25/hr

Strong experience with Kalman Filtering and sensor fusion (IMU, encoders, LiDAR, F/T sensors) for ... Navigation Guru: Deep familiarity with the stack, including custom plugin development (Controller ...

Firefly Aerospace

GNC Engineer II

Cedar Park, TX · On-site

... guidance, navigation, and control, or related technical discipline * Understanding of launch ... Knowledge of state estimation techniques including Kalman filtering, sensor fusion, and covariance ...

Firefly Aerospace

GNC Engineer II

Cedar Park, TX · On-site

... guidance, navigation, and control, or related technical discipline * Understanding of launch ... Knowledge of state estimation techniques including Kalman filtering, sensor fusion, and covariance ...

Firefly Aerospace

GNC Engineer II

Cedar Park, TX · On-site

... guidance, navigation, and control, or related technical discipline * Understanding of launch ... Knowledge of state estimation techniques including Kalman filtering, sensor fusion, and covariance ...

Apptronik

Sr. Software Engineer - Wheeled Controls

Austin, TX · On-site

$121K - $160K/yr

Strong experience with Kalman Filtering and sensor fusion (IMU, encoders, LiDAR, F/T sensors) for ... Navigation Guru: Deep familiarity with the stack, including custom plugin development (Controller ...

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Kalman Filtering Inertial Navigation information

What are some common challenges faced when implementing Kalman Filtering for inertial navigation systems?

One common challenge in this role is managing sensor noise and drift, which can significantly affect the accuracy of inertial navigation solutions. You'll need to carefully tune filter parameters and sometimes integrate additional sensor data (like GPS or magnetometers) to improve robustness. Collaboration with hardware teams is typical, as understanding sensor characteristics is crucial for optimal filter performance. Additionally, real-time processing constraints often require you to optimize algorithms for efficiency without sacrificing accuracy.

What are the key skills and qualifications needed to thrive as a Kalman Filtering Inertial Navigation Engineer, and why are they important?

To thrive as a Kalman Filtering Inertial Navigation Engineer, you need a solid background in control systems, signal processing, and estimation theory, generally supported by a degree in electrical engineering, aerospace engineering, or a related field. Proficiency with MATLAB, Python, sensor fusion algorithms, and experience implementing Kalman filters in embedded systems are typically required. Strong analytical thinking, attention to detail, and effective communication skills help professionals collaborate across multidisciplinary teams and solve complex problems. These skills and qualifications are vital to ensure accurate navigation solutions and robust system performance in real-world applications.

What is Kalman Filtering in inertial navigation?

Kalman Filtering in inertial navigation refers to the use of a mathematical algorithm—the Kalman filter—to estimate the position, velocity, and orientation of a moving object by processing data from inertial sensors such as accelerometers and gyroscopes. The Kalman filter improves the accuracy of navigation by optimally combining sensor measurements and correcting for errors and noise. This technique is essential in applications like aerospace, robotics, and autonomous vehicles, where precise movement tracking is required. By continuously updating estimates as new sensor data arrives, Kalman filtering helps provide reliable and real-time navigation solutions.

What is the difference between Kalman Filtering Inertial Navigation vs INS Algorithm Developer?

AspectKalman Filtering Inertial NavigationINS Algorithm Developer
CredentialsEngineering degrees, knowledge of Kalman filters, navigation systemsEngineering degrees, expertise in navigation algorithms, sensor fusion
Work EnvironmentResearch labs, aerospace, defense, autonomous vehicle developmentSoftware development, simulation, embedded systems in similar industries
Industry UsageDesign and implementation of navigation systems using Kalman filtersDeveloping algorithms for inertial navigation systems, improving accuracy

Kalman Filtering Inertial Navigation focuses on applying Kalman filters to process sensor data for navigation accuracy, while INS Algorithm Developers design and optimize algorithms for inertial navigation systems. Both roles require similar technical skills but differ in their primary focus: one on filtering techniques, the other on algorithm development.

What are popular job titles related to Kalman Filtering Inertial Navigation jobs in Texas? For Kalman Filtering Inertial Navigation jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Kalman Filtering Inertial Navigation jobs in Texas look for? The top searched job categories for Kalman Filtering Inertial Navigation jobs in Texas are:
Kalman Filtering Inertial Navigation jobs near you
Infographic showing various Kalman Filtering Inertial Navigation job openings in Texas as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.
Principal Engineer, State Estimation (Dallas, TX)

Principal Engineer, State Estimation (Dallas, TX)

Shield AI

Dallas, TX

$274K - $411K/yr

Full-time

Posted 7 days ago

Job description

Founded in 2015, 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 and V-BAT and X-BAT aircraft. 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, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

Job Description:
As a Principal State Estimation Engineer, you will play a key role driving the development, optimization, and deployment of advanced sensor fusion algorithms for autonomous UAV navigation in dynamic and contested environments. You will design and implement real-time sensor processing pipelines, integrate multi-sensor data for robust navigation and state estimation, and collaborate closely with autonomy researchers, software engineers, and hardware teams to ensure seamless system performance.  
 
Your expertise will contribute to transitioning cutting-edge research into deployable solutions, helping Shield AI push the boundaries of UAV autonomy and situational awareness. 
What you'll do:
  • Develop and implement advanced state estimation algorithms, including inertial navigation, sensor fusion, and alternative navigation techniques for denied environments. 
  • Design and optimize state estimation frameworks to integrate data from IMUs, GNSS receivers, visual odometry, magnetometers, barometers, and radar systems. 
  • Build real-time sensor processing pipelines for UAV platforms, focusing on robustness, accuracy, and failover performance. 
  • Collaborate with autonomy, software, and hardware teams to ensure seamless integration of state estimation components within larger autonomous systems. 
  • Lead simulation, lab testing, and field validation of state estimation algorithms to assess performance under varying operational conditions. 
  • Stay on the forefront of navigation and state estimation innovation-adapting emerging technologies and research into deployable, mission-ready solutions. 
Required qualifications:
  • Typically requires a minimum of 12 years of relevant experience with a bachelor's degree; or 10 years with a master's degree; or a PhD with 8 years of experience; or equivalent practical experience. 
  • Deep experience developing real-time navigation and/or sensor fusion algorithms with IMUs, GPS, and other sensors. 
  • Strong understanding of state estimation techniques (e.g., Kalman filters, extended and unscented variants, particle filters, etc.). 
  • Proficiency with C++11 or newer; experience with real-time operating environments. 
  • Comfort with Linux, scripting, and standard development tools. 
  • Excellent communication and collaboration skills; ability to work across engineering disciplines and with external partners. 
  • Proven track record of successfully shipping products, showcasing the ability to navigate through development cycles, overcome obstacles, and deliver high-quality solutions to meet project deadlines and exceed expectations in a fast-paced environment.  
  • You have a demonstrated record of working hard, being a trustworthy teammate, holding yourself and others to high standards, and being kind to others. 
Preferred qualifications:
  • Experience developing and implementing inertial navigation solutions for GPS-denied or degraded environments. 
  • Knowledge of computer vision techniques  
  • Proficiency in optimizing algorithms for compute-constrained systems  
  • Experience with CUDA or other hardware acceleration technologies (e.g. FPGAs)  
  • Proven track record of transitioning from R&D to production 
$274,560 - $411,840 a year
#LI-JM2
#LF

Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
 
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
 
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 to 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. 
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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