ZipRecruiter

Log In

1

Kalman Filter Estimation Jobs (NOW HIRING)

Anduril Industries

GNC Engineer

Seattle, WA

High-fidelity state estimation using various Kalman filter types (Error-State, Invariant Filters) * Fusion of diverse sensor modalities (IMU, EO/IR, Baro, ToF, Radar Altimeter, Star Trackers) You'll ...

Anduril Industries

Senior GNC Engineer

Seattle, WA

$118K - $163K/yr

High-fidelity state estimation using various Kalman filter types (Error-State, Invariant Filters) * Fusion of diverse sensor modalities (IMU, EO/IR, Baro, ToF, Radar Altimeter, Star Trackers) You'll ...

Slope

Senior GNC Engineer

Seattle, WA · On-site

$132 - $198/hr

High-fidelity state estimation using various Kalman filter types (Error-State, Invariant Filters) * Fusion of diverse sensor modalities (IMU, EO/IR, Baro, ToF, Radar Altimeter, Star Trackers) You'll ...

next page

Showing results 1-20

All JobsKalman Filter Estimation Jobs

Kalman Filter Estimation information

See salary details

$20K

$84.6K

$129.5K

How much do kalman filter estimation jobs pay per year?

As of Aug 9, 2026, the average yearly pay for kalman filter estimation in the United States is $84,586.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,000.00 and $98,500.00 per year, depending on experience, location, and employer.

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 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 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 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.
More about Kalman Filter Estimation jobs
What cities are hiring for Kalman Filter Estimation jobs? Cities with the most Kalman Filter Estimation job openings:
What states have the most Kalman Filter Estimation jobs? States with the most job openings for Kalman Filter Estimation jobs include:
What job categories do people searching Kalman Filter Estimation jobs look for? The top searched job categories for Kalman Filter Estimation jobs are:
Kalman Filter Estimation jobs near you
Infographic showing various Kalman Filter Estimation job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Hybrid job distribution, with an average salary of $84,586 per year, or $40.7 per hour.

Senior Navigation Engineer with Security Clearance

IDR, Inc

Denver, CO • On-site

$115K/yr

Other

Re-posted 23 days ago

Job description

IDR is seeking a Senior Navigation Engineer to join one of our top clients for an opportunity in Westminster, CO. This role supports spaceflight missions across all phases of spacecraft navigation, from estimation and tracking architecture development to flight operations readiness and real-time performance support. You will help advance state estimation capabilities through sophisticated Kalman filter development and validation while partnering with teams across mission engineering and verification activities. Position Overview for the Senior Navigation Engineer: Lead spacecraft navigation for all mission phases, including formulation, tracking architecture development, estimation approach, and operations.
Develop and validate advanced Kalman filter configurations for complex regimes, such as multi-body, low-thrust, and weak observability scenarios.
Serve as primary navigation lead for flight operations prep, including console support, real-time orbit determination, and anomaly response.
Mentor junior engineers and drive mission-critical navigation analysis, system-level trades, and verification/validation activities.
Requirements for the Senior Navigation Engineer: 5–12 years of professional experience in spacecraft navigation, orbit determination, or closely related flight dynamics roles.
Bachelor’s degree in Aerospace Engineering, Systems Engineering, or related field.
Demonstrated leadership of OD campaigns or major navigation tasks, including filter setup, force models, and tracking strategies.
Proven ability to design and adapt Kalman filters for new dynamical and tracking regimes, including dynamic, bias, stochastic, and consider parameters.
Significant experience with navigation/astrodynamics tools (e.g., MONTE, FreeFlyer, ODTK, GMAT, STK) in flight or flight-like applications. $115k-174,900k/year

Apply