About the Job
EDGE is an advanced technology group focused on developing disruptive solutions for defense and beyond. We are committed to solving real-world challenges by rapidly bringing innovative technologies and services to market. With a strong emphasis on collaboration and creativity, we leverage advanced technologies such as autonomous capabilities, cyber-physical systems, directed energy, and artificial intelligence to transform the defense industry.
As part of our initiative Advanced Concepts, we invite you to join us in enabling a secure future.
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Key Accountabilities
- Support the creation of mathematical models for flight dynamics and control systems of aerial platforms and missiles, using knowledge of differential equations and system theory under various operational conditions.
- Assist in the innovation and refinement of Guidance, Navigation, and Control (GNC) algorithms for aerospace vehicles, applying both classical and modern control theory principles, including PID, state feedback, adaptive control, and robust control strategies.
- Collaborate in implementing algorithms that enhance the precision, stability, and overall performance of flight control systems, particularly during all phases of flight.
- Contribute to the design and analysis of systems for effective endgame targeting and the development of midcourse guidance strategies, incorporating trajectory shaping and threat avoidance for optimized mission outcomes.
- Utilize knowledge of flight control algorithms such as PID controllers, state estimation (e.g., Kalman filtering), path planning, and obstacle avoidance.
- Apply foundational AI and ML techniques, including deep learning and reinforcement learning, to optimize mission planning, threat assessment, and real-time decision-making in aerospace operations.
- Support the development of decentralized swarming algorithms grounded in AI principles such as graph theory and game theory, which enhance the scalability and fault tolerance of swarm operations.
- Specialized knowledge in the Pixhawk Flight Controller, including familiarity with the Pixhawk architecture, the software development framework (PX4 or Ardupilot), and related tools (QGroundControl or Missionplanner).
Knowledge/Qualification & Experience
- A minimum of 4 years of experience in control engineering, with exposure to flight dynamics, control system design, and the application of AI/ML in navigation or related fields.
- Bachelor's or Master’s degree in Aerospace Engineering, Electrical Engineering, Computer Science, or related fields, with specialization in control systems, flight dynamics, or applied mathematics.
- Solid understanding of aerospace system dynamics, control theory, and aerodynamics.
- Proficient knowledge in aerodynamics, propulsion, and flight dynamics related to missile and unmanned aerial vehicle (UAV) systems.
- Strong proficiency in simulation and modeling tools (e.g., MATLAB/Simulink, ANSYS or similar), programming languages (C/C++, Python, Julia), and AI/ML frameworks (TensorFlow, PyTorch).
- Demonstrated experience with AI/ML techniques relevant to aerospace operations and a willingness to learn and apply advanced methods.
