ZipRecruiter

Log In

1

Kalman Filter Estimation Jobs in California (NOW HIRING)

Shield AI

Senior Manager, Perception (R3634)

San Diego, CA · On-site

$103K - $130K/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.

next page

Showing results 1-20

All JobsKalman Filter Estimation JobsKalman Filter Estimation Jobs in California

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 California?

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

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

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

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

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

Kalman Filter Estimation jobs near you
Infographic showing various Kalman Filter Estimation job openings in California as of August 2026, with employment types broken down into 83% Full Time, 15% Part Time, 1% Contract, and 1% Nights. Highlights an 97% Physical, and 3% Remote job distribution.

Senior State Estimation Engineer

Hayden AI

San Francisco, CA • On-site

$200K - $260K/yr

Full-time

Re-posted 13 days ago

Job description

About Us
At Hayden AI, we are on a mission to harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges.
From bus lane and bus stop enforcement to transportation optimization technologies and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive toward a sustainable future.
What the job involves
As a Senior State Estimation Engineer at Hayden AI, you will be asked to derive and implement novel real-time pose estimation algorithms. Research, develop and implement algorithms to solve large-scale mapping. Collaborate with other engineers to develop algorithms for in-situ and in-factory multi-sensor calibration.
Responsibilities
  • Contribute to high impact, multidisciplinary projects across teams
  • Program and develop software in C++ and/or python
  • Derive and implement novel, real-time pose estimation algorithms
  • Research, develop and implement algorithms to solve problems such as large-scale mapping, probabilistic object tracking, online/offline sensor calibration and/or vision-based localization
  • Collaborate with deep learning, device, and cloud teams to improve overall system architectures
  • Provide mentorship to our junior engineers

Required Qualifications
  • Master of Science degree or the foreign equivalent in Electrical and Computer Engineering, Robotics, Machine Learning, Computer Science, Electrical Engineering or a related field.
  • Five (5)+ years of experience in the position offered, as a software engineer, software engineer intern, or a related state estimation engineer role.
  • Five (5) years of experience with all of the following: programming in C++; designing and developing software; classical ML, Linear Algebra,
    Stochastic Processes, Geometric Computer Vision and Optimization (Convex, Nonlinear); Kalman Filter, MAP, Sequential Monte Carlo (particle
    filter), Nonlinear Least squares, IRLS and MHT; GPS, IMU, camera and wheel odometry.
  • Experience deploying SLAM/VIO estimators in a real-world application.
  • Work with multiple sensors such as GPS, IMU, camera, LIDAR, and wheel odometry.

Apply