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State Estimation Engineer - Autonomy

USA Tech Recruit

Overview We’re working with a well-funded startup transforming the defence industry looking for a State Estimation Engineer, who will be responsible for designing, implementing, and optimizing algorithms that provide accurate and reliable state estimation for autonomous aerial systems. This role requires close collaboration with both hardware and software teams to ensure robust performance across diverse operational scenarios. This is a full time, onsite position in El Segundo, CA and you must be a US citizen and able to obtain US top secret security clearance to apply for this position . Key Responsibilities Design and implement state estimation algorithms, including multi-sensor fusion for IMUs, GPS, cameras, and other onboard sensors. Develop and deploy real-time software for embedded platforms. Test and validate algorithms in both simulated and real-world environments. Diagnose and improve estimation performance under challenging conditions such as sensor noise, environmental interference, and hardware limitations. Collaborate with autonomy, controls, and perception teams to integrate state estimation into navigation and guidance systems. Keep up to date with advancements in state estimation, robotics, and related research fields. Key Qualifications 3+ years of experience developing state estimation algorithms for robotics, UAVs, or similar autonomous systems. Strong background in sensor fusion methods (e.g., Kalman filter variants, particle filters). Proficiency in C++ or Python. Experience with embedded or real-time computing environments. Familiarity with IMU, GPS, camera, and lidar sensors. Solid understanding of linear algebra, probability, and optimization techniques. Experience with simulation tools such as Gazebo or Mujoco. By applying to this role you understand that we may collect your personal data and store and process it on our systems. For more information please see our Privacy Notice #J-18808-Ljbffr USA Tech Recruit

Vacancy posted 4 days ago
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