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Kalman Filter System Identification Engineer Jobs

Pronto.ai, Inc.

Robotics Controls Engineer

San Francisco, CA · On-site

$98K - $127K/yr

About the Role We're looking for a Robotics Controls Engineer to develop and maintain the core ... Develop system identification scripts for auto-tuning controllers * Develop a Kalman filter that ...

ANDURIL INDUSTRIES

Senior GNC Engineer

Seattle, WA

$132K - $198K/yr

Anduril's family of systems is powered by Lattice OS, an AI-powered operating system that turns ... High-fidelity state estimation using various Kalman filter types (Error-State, Invariant Filters)

Advanced Space

Sr. Navigation Engineer

Westminster, CO · On-site

$132K - $174K/yr

Develop and validate advanced Kalman filter configurations for complex regimes (multi-body, low ... Bachelor's degree in Aerospace Engineering, Systems Engineering, or related field. * Demonstrated ...

Advanced Space

Sr. Navigation Engineer

Westminster, CO · On-site

$132K - $174K/yr

Develop and validate advanced Kalman filter configurations for complex regimes (multi-body, low ... Bachelor's degree in Aerospace Engineering, Systems Engineering, or related field. * Demonstrated ...

Anduril Industries

Senior GNC Engineer

Seattle, WA

$118K - $163K/yr

High-fidelity state estimation using various Kalman filter types (Error-State, Invariant Filters ... Experience with modeling and simulation of dynamic systems and sensor phenomenology. * Eligible to ...

Anduril Industries

Senior GNC Engineer

Seattle, WA · On-site

$118K - $163K/yr

Anduril's family of systems is powered by Lattice OS, an AI-powered operating system that turns ... High-fidelity state estimation using various Kalman filter types (Error-State, Invariant Filters)

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All JobsKalman Filter System Identification Engineer Jobs

Kalman Filter System Identification Engineer information

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$53.5K

$127.2K

$167K

How much do kalman filter system identification engineer jobs pay per year?

As of Jun 7, 2026, the average yearly pay for kalman filter system identification engineer in the United States is $127,215.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,000.00 and $157,000.00 per year, depending on experience, location, and employer.

What are Kalman Filter System Identification Engineers?

Kalman Filter System Identification Engineers are specialized professionals who design, implement, and optimize algorithms that use Kalman filters for estimating and identifying the dynamic behavior of systems. Their work involves using mathematical models and sensor data to predict and correct system states in real time, which is essential in fields like aerospace, robotics, and control systems. These engineers often collaborate with multidisciplinary teams to ensure accurate system modeling, noise reduction, and performance improvement in complex environments.

What is the difference between Kalman Filter System Identification Engineer vs Control Systems Engineer?

AspectKalman Filter System Identification EngineerControl Systems Engineer
CredentialsBachelor's or Master's in Electrical, Mechanical, or Systems Engineering; knowledge of Kalman filtersBachelor's or Master's in Electrical, Mechanical, or Control Engineering; expertise in control theory
Work EnvironmentResearch labs, aerospace, robotics, automotive industriesManufacturing, automation, aerospace, industrial systems
Industry UsageSensor fusion, state estimation, system modelingSystem design, control algorithm development, automation

While both roles require a strong engineering background, the Kalman Filter System Identification Engineer specializes in developing and applying Kalman filters for system modeling and state estimation. In contrast, the Control Systems Engineer focuses on designing and implementing control algorithms to regulate system behavior. Both roles often collaborate but serve distinct functions within engineering projects.

What are some common challenges faced by Kalman Filter System Identification Engineers when working with real-world data?

One frequent challenge for Kalman Filter System Identification Engineers is dealing with noisy, incomplete, or non-linear data from real-world sensors. Tuning filter parameters and accurately modeling system dynamics can require significant iteration and domain expertise, especially when system behavior deviates from theoretical assumptions. Collaboration with cross-functional teams—such as hardware engineers and data scientists—is often essential to refine models, validate assumptions, and ensure robust filter performance. Engineers in this role may also need to balance computational efficiency with estimation accuracy, particularly for real-time applications.

What are the key skills and qualifications needed to thrive as a Kalman Filter System Identification Engineer, and why are they important?

To thrive as a Kalman Filter System Identification Engineer, you need a solid background in control systems, signal processing, and statistical estimation, often supported by a degree in electrical engineering, aerospace engineering, or applied mathematics. Proficiency with MATLAB, Simulink, Python, and familiarity with system identification toolboxes and Kalman filtering algorithms is essential. Strong analytical thinking, problem-solving abilities, and effective communication skills help you interpret data and collaborate with multidisciplinary teams. These skills are crucial for developing robust estimation algorithms that ensure accurate system modeling and reliable real-time performance.

Robotics Controls Engineer

Pronto.ai, Inc.

San Francisco, CA • On-site

$98K - $127K/yr

Full-time

Posted 24 days ago

Job description

About Pronto
While most Autonomous Vehicle (AV) technology companies are stuck in R&D mode, Pronto is a world-leader in commercializing AV tech via our Autonomous Haulage System, which is automating haulage operations at mines and quarries around the world. Pronto's team of Silicon Valley veterans has been at the forefront of every major AV development over the past 20 years, with a relentless focus on commercializing the technology, leading to our current specialization in off-road applications. This focus and our decades of experience have put Pronto on a track to become the world's first profitable AV technology company.
Our first product is an Autonomous Haulage System (AHS) that enables mines, quarries, and construction sites to deploy autonomous vehicles inside their existing operations to improve site safety and add efficiency gains.
About the Role
We're looking for a Robotics Controls Engineer to develop and maintain the core control systems that enable autonomous haul trucks to operate safely in mining environments. You'll work on localization, path following, longitudinal control, and steering systems that run on 200+ ton vehicles.
What You'll Build
  • Localization & State Estimation
  • Longitudinal Control
  • Lateral Control
  • Navigation

Responsibilities
  • Design, implement, and tune control algorithms for autonomous vehicle systems
  • Develop state estimation pipelines that fuse multiple sensor modalities
  • Analyze system performance through simulation and field testing
  • Debug control issues using logged data and identify root causes
  • Collaborate with perception, planning, and hardware teams to integrate control systems
  • Write production-quality Python code that runs reliably and efficiently
  • Travel note: This role requires periodic travel to customer sites (up to 15%)
  • Schedule note: Some schedule flexibility may be required during deployments

Required Qualifications
  • BS/MS/PhD in Robotics, Mechanical Engineering, Aerospace Engineering, Electrical Engineering or related field
  • 2+ years of professional (non-internship) software development experience
  • Strong foundation in classical control theory (PID, lead/lag compensation, stability analysis)
  • Experience with state estimation (Kalman filters, EKF/UKF)
  • Proficiency in Python and NumPy/SciPy for numerical computing
  • Understanding of vehicle dynamics and kinematics
  • Ability to read and debug real-time control code
  • Experience deploying localization and controls algorithms on real-world systems

Preferred Qualifications
  • Experience with Model Predictive Control (MPC)
  • Familiarity with path following algorithms (Stanley, Pure Pursuit)
  • Background in signal processing and filter design
  • Knowledge of system identification techniques
  • Experience with heavy equipment or off-highway vehicles
  • Knowledge of CAN bus and vehicle interfaces
  • ROS or similar robotics middleware experience
  • Familiarity with modern ML techniques for controls problems

Technical Environment
  • Languages: Python (primary), C++ (optimization-critical paths)
  • Libraries: NumPy, SciPy
  • Hardware: NVIDIA Jetson, GPS/RTK, IMUs, CAN interfaces
  • Testing: Field testing on haul trucks, log replay, simulation

Example Projects
  • Tune longitudinal controller gains for a new 100-ton truck platform accounting for varying payload (0-80 tons) and grade (-15% to +15%)
  • Implement anti-windup and bumpless transfer for switching between throttle and brake control modes
  • Create simulations to facilitate control design and continuous integration
  • Develop system identification scripts for auto-tuning controllers
  • Develop a Kalman filter that gracefully handles GPS dropouts using IMU dead reckoning

Pronto is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

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