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Salary
$173k – $250k per year
Location
Remote (United States)
Seniority
Staff · 7+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Shield AI is an American defence technology company founded in 2015 that builds autonomy software and uncrewed aircraft for military missions. Its Hivemind autonomy stack lets aircraft fly, navigate and complete objectives without GPS, a remote pilot or a communications link, which matters in contested environments where those links are jammed. Headquartered in San Diego, California, the company fields the V-BAT vertical take-off aircraft with United States and allied forces, licenses Hivemind to other manufacturers and is developing the X-BAT jet for high-end missions.

The Guidance Navigation Control engineering team focuses on researching and developing state-of-the-art algorithms that drive high-performance flight for a blue-sky project.. As a GNC Engineer on this team, you’ll work on an agile team grounded in first principles to push the boundaries of the state-of-the-art.

Required Qualifications:

  • BS in Aerospace, Aeronautical, Mechanical, Electrical, or Software Engineering with a focus on Control Systems
  • Minimum of 7 years of related experience with a Bachelor’s degree; or 6 years and a Master’s degree; or 4 years with a PhD; or equivalent work experience in the area of vehicle dynamics modeling, flight controls, or simulation.
  • Experience with C++ in a production environment
  • Experience with Matlab and Simulink
  • Expert knowledge of aircraft dynamics and control, stability, and handling qualities
  • Experience tuning and optimizing control systems in simulation and real-world
  • Passion for solving complex problems in a fast-moving environment
  • Demonstrated record of working hard, strong communication skills, being a trustworthy teammate, and being kind to others
  • Ability to obtain a SECRET clearance

Preferred Qualifications:

  • MS or PhD in Aerospace, Aeronautical, Mechanical, Electrical, or Software Engineering with a focus on Control Systems
  • Experience with Modern Control Theory, e.g. LQR/LQG, Adaptive Control, Robust Control, Model Predictive Control (MPC), etc.
  • Proficient with extracting linear aircraft state space models from nonlinear equations of motion
  • Proficient with design or selection of servos, inertial navigation systems, air data units, vision-based navigation systems
  • Familiarity with Kalman Filters
  • Familiarity with system identification techniques
  • Familiarity with git, continuous integration & delivery, etc.
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