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Kalman Filtering Inertial Navigation Jobs (NOW HIRING)

Understanding of vehicle dynamics and experience with inertial navigation systems * Familiarity ... Experience with state estimation and filtering methods such as Kalman or particle filters ...

Understanding of vehicle dynamics and experience with inertial navigation systems * Familiarity ... Experience with state estimation and filtering methods such as Kalman or particle filters ...

Understanding of vehicle dynamics and experience with inertial navigation systems * Familiarity ... Experience with state estimation and filtering methods such as Kalman or particle filters ...

Understanding of vehicle dynamics and experience with inertial navigation systems * Familiarity ... Experience with state estimation and filtering methods such as Kalman or particle filters ...

Understanding of vehicle dynamics and experience with inertial navigation systems * Familiarity ... Experience with state estimation and filtering methods such as Kalman or particle filters ...

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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.

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What states have the most Kalman Filtering Inertial Navigation jobs? States with the most job openings for Kalman Filtering Inertial Navigation jobs include:
Infographic showing various Kalman Filtering Inertial Navigation job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.
Forward Deployed Robotics Engineer

Forward Deployed Robotics Engineer

Gecko Robotics

Pittsburgh, PA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted yesterday


Job description

What We Do

Gecko Robotics is helping the world’s most important organizations ensure the availability, reliability, and sustainability of critical infrastructure. Gecko's complete and connected solutions combine wall-climbing robots, industry-leading sensors, and an AI-powered data platform to provide customers with a unique window into the current and future health of their physical assets. This enables real-time decision making to increase the efficiency and safety of operations, promote mission readiness, and protect the environment and civilization from the effects of infrastructure failure.

Role at a Glance
We are seeking a highly skilled Robotics Engineer specializing in underwater sensor fusion and localization to lead the development and deployment of robust navigation systems for our hull-cleaning and NDT inspection robots. The ideal candidate will have deep expertise in fusing data from underwater sensor suites - including IMUs, DVLs, pressure sensors, acoustic positioning systems such as USBL/LBL, and sonar-based relative sensing - to produce accurate and reliable state estimates in GPS-denied, close-to-structure environments. You will be responsible for solving real localization problems in the field: compensating for drift, handling intermittent or delayed aiding, managing sensor dropouts and acoustic outliers, and delivering pragmatic solutions that can be deployed under tight timelines.

To be successful in this role, you must possess strong hands-on experience designing and implementing advanced filtering algorithms for real-world robotic systems, such as error-state Extended Kalman Filters (EKF), Unscented Kalman Filters (UKF), and Particle Filters where appropriate. You should be adept at deriving and maintaining both linear and nonlinear state-space models to continuously estimate critical variables such as position, velocity, attitude, and sensor biases in challenging underwater conditions. Additionally, the role requires expertise in calibrating and validating real sensor stacks - including IMU bias estimation, DVL alignment and dropout handling, pressure-depth offsets, acoustic latency, and timing synchronization - as well as a strong understanding of underwater navigation concepts such as dead reckoning, inertial navigation, observability in constrained motion, degraded-mode localization, and robust fusion when absolute aids are sparse or unreliable.

Required Skills and Expertise:
  • Advanced Filtering Algorithms: Proficiency designing and implementing localization and navigation filters, including Kalman Filters, error-state Extended Kalman Filters (EKF), Unscented Kalman Filters (UKF), and Particle Filters when warranted by the sensing environment or failure modes.

  • Underwater Multi-Sensor Integration: Experience fusing data from complementary and redundant underwater sensors, including IMUs, DVLs, pressure sensors, USBL/LBL systems, sonar-derived relative measurements, and other non-vision localization inputs to improve robustness and reliability.

  • State-Space Modeling & Observability: Strong background in formulating continuous-time and discrete-time dynamic models for underwater vehicles, including position, linear/angular velocity, attitude, sensor biases, and other latent states, with an understanding of observability under constrained motion and close-proximity operations.

  • Sensor Calibration, Timing & Noise Management: Expertise in managing real-world uncertainties such as drifting IMU biases, DVL misalignment or bottom-lock loss, pressure sensor offsets, acoustic multipath and latency, clock synchronization issues, and magnetic disturbances near large steel structures.

  • Underwater Navigation: Thorough understanding of GPS-denied underwater localization concepts, including dead reckoning, inertial navigation, acoustic aiding, hull-relative localization, and fallback behavior when absolute position updates are unavailable or degraded.

  • Forward-Deployed Problem Solving: Demonstrated ability to deploy working sensor fusion solutions within tight timelines, debug failures from field logs and replay tools, tune estimators under operational pressure, and make practical engineering tradeoffs to keep systems moving forward.

  • Fusion System Design: Familiarity designing resilient localization architectures that can tolerate delayed and asynchronous measurements, intermittent aiding, sensor dropouts, and compute or bandwidth constraints common in deployed underwater robotic systems.

Who We Are

At Gecko, our people are our greatest investment. In addition to competitive compensation packages, we offer company equity, 401(k) matching, gender-neutral parental leave, full medical, dental, and vision insurance, mental health, ongoing professional development, family planning assistance, and flexible paid time off. 

Gecko values collaboration, innovation, and partnership, and we believe we do our best work when we're together in person. We’re an office-first culture but understand that sometimes you may need to work from home. Many people are in the office five days a week, others need a bit more flexibility. Ultimately, we care about the outcomes we achieve - and creating a culture of autonomy and trust that enables that impact.

Gecko is committed to creating a culture of inclusion and belonging, and we are proud to be an equal opportunity employer.  We believe it is our collective responsibility to uphold these values and encourage candidates from all backgrounds to join us in our mission to protect today’s infrastructure and give form to tomorrow’s. All qualified applicants will be treated with respect and receive equal consideration for employment without regard to race, color, creed, religion, sex, gender identity, sexual orientation, national origin, disability, uniform service, veteran status, age, or any other protected characteristic per federal, state, or local law. If you are passionate about what you do and want to use your talents to support our critical mission, we’d love to hear from you.