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Shield AI

Builds autonomous aircraft for defense

State Estimation Engineer

Flight Dynamics & GNCUpdated on Nov 14
Full-timeDallas, TX, USAIn-person

About the Job

Requirements

  • Typically requires at least 3 years of relevant experience with a bachelor's degree, 2 years with a master's degree, 1 year with a PhD, or equivalent practical experience.
  • Familiarity with algorithms.
  • Proficiency in C++11 or newer in real-time environments.
  • Comfort working in Linux, with experience using standard command-line tools and scripting.
  • Strong written and verbal communication skills and a collaborative mindset.
  • Demonstrated success working in fast-paced development cycles and delivering high-quality results.

Responsibilities

  • Develop and implement real-time state estimation algorithms, including inertial navigation, sensor fusion, and alternative navigation methods for GPS-denied or degraded environments.
  • Integrate data from IMUs, GNSS receivers, visual odometry, magnetometers, barometers, and radar into robust estimation frameworks.
  • Design sensor processing pipelines focused on accuracy, robustness, and system-level fault tolerance.
  • Collaborate with autonomy, software, and hardware teams to ensure end-to-end integration of navigation and PNT systems.
  • Conduct simulation, lab testing, and field trials to evaluate algorithm performance under real-world conditions.
  • Stay current on advancements in state estimation and navigation technologies and help adapt new innovations into deployable solutions.

Desired Qualifications

  • Experience developing and deploying real-time navigation or sensor fusion algorithms using IMUs, GPS, or other sensors.
  • Strong understanding of filtering and estimation techniques, such as Kalman filters, EKF, UKF, and particle filters.
  • Experience implementing inertial navigation algorithms in degraded or GPS-denied conditions.
  • Exposure to visual odometry or computer vision-based navigation approaches.
  • Experience optimizing code for performance on compute-constrained platforms.
  • Familiarity with CUDA or hardware acceleration techniques such as FPGAs.
  • Experience transitioning navigation solutions from research into production environments.

About the Company

Shield AI

Builds autonomous aircraft for defense

Shield AI builds autonomous aircraft and flight software for military and allied defense customers, with a focus on operations where conventional remote control breaks down. Its Hivemind AI pilot handles decisions during a mission, while the V-BAT aircraft gathers intelligence and locates targets. Aircraft makers use its software tools to develop and test their own autonomy, and its Aechelon business supplies visual and sensor simulation for pilot training. The company earns money from aircraft sales, autonomy software and contracted engineering and operational services. Shield AI was founded in 2015 and is headquartered in San Diego, California.

Company size
1,001-5,000
Company stage
Debt Financing
Total funding
$4.8B
Headquarters
San Diego, CA
Founded
2015

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