Object Detection and Tracking Engineer
Shield AI is a U.S. defense-technology company developing mission-autonomy software and autonomous aircraft for military and allied operations.
Funding history
Investors
About Shield AI
Founded in 2015, Shield AI builds Hivemind autonomy software and V-BAT and X-BAT aircraft for operations in contested, GPS- and communications-denied environments. Its current site also presents Aechelon synthetic-reality simulation and Vision Systems detection and tracking products.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will develop real-time object detection, classification, tracking, sensor-fusion, and state-estimation algorithms for autonomous aircraft. You will optimize and validate perception pipelines in simulation and operational settings, integrate sensor data and outputs with autonomy systems, and support hardware integration and flight-related testing.
Requirements
- Bachelor's, master's, or PhD degree in a relevant engineering discipline, or equivalent practical experience
- 10 years of related experience with a bachelor's degree, 9 years with a master's degree, or 7 years with a PhD
- Experience implementing Kalman filters, multi-target tracking, or deep-learning detection models
- Familiarity with radar and EO/IR sensor fusion
- Familiarity with SLAM, visual-inertial odometry, or sensor-fused localization
- Ability to work with interface control documents and hardware integration specifications
- Proficiency in version control, debugging, and test-driven development
Responsibilities
- Develop algorithms for object detection, classification, and multi-target tracking
- Implement sensor-fusion frameworks using vision, radar, and mission-sensor data
- Develop localization and pose-estimation algorithms using IMU, GPS, vision, and onboard sensors
- Interpret sensor interface control documents and technical specifications
- Optimize perception pipelines for real-time performance and robustness
- Integrate perception outputs with planning, behavior, and decision-making modules
- Validate algorithms using synthetic data, simulation, field testing, and operational environments
- Integrate perception algorithms with onboard compute platforms and sensor payloads
- Contribute advanced airborne-sensing techniques
- Travel 10–15% of the year