We are seeking a highly skilled GNC Engineer to lead the design, implementation, and validation of advanced flight control and navigation laws for a high-performance, long-range autonomous UAV platform. You will be responsible for the full GNC stack—from high-fidelity 6-DOF modeling to the deployment of robust guidance algorithms in GNSS-denied and contested environments. The ideal candidate bridges the gap between theoretical aerospace control and real-time embedded implementation.
Key Responsibilities And Accountabilities
Guidance Law Development: Design and implement Advanced Guidance Laws (e.g., Optimal Guidance, Proportional Navigation variants) for all mission phases, including mid-course transit and high-precision terminal engagement.
Navigation & State Estimation: Develop robust state estimation filters (EKF/UKF) that fuse data from IMUs, Air Data Systems, and Terrain-Referenced Navigation (TRN) or Vision-based updates to maintain PNT resilience without GPS.
Flight Dynamics & Modeling: Create and maintain high-fidelity 6-DOF (Degrees of Freedom) vehicle models and flight simulations to predict performance across a wide flight envelope.
Control Loop Design: Architect and tune multi-loop flight control systems for stability and performance, accounting for aero-elasticity, varying CG (Center of Gravity), and external disturbances.
Path Planning & Trajectory Optimization: Implement algorithms for long-range energy-efficient routing, obstacle avoidance, and dynamic re-tasking in complex 3D environments.
Validation & Flight Test: Conduct extensive SITL/HITL simulations to validate GNC performance. Analyze flight test data to refine control parameters and verify "miss-distance" or "arrival-accuracy" requirements.
Qualifications
Bachelor’s or Master’s (PhD preferred) in Aerospace Engineering, Robotics, or a related field with a focus on Control Theory.
3–5+ years in GNC engineering, specifically working on autonomous aircraft, missiles, or high-speed UAVs.
Skills And Abilities
Control Theory: Expert knowledge of Classical (PID, Root Locus) and Modern (LQR/LQG, Robust Control, MPC) control systems.
Mathematics: Deep understanding of Linear Algebra, Quaternion math, Coordinate Transformations, and vehicle dynamics.
Software: Proficiency in C++ (for real-time deployment) and MATLAB/Simulink (for modeling and filter design). Experience with Python for data analysis.
Ecosystems: Familiarity with the PX4 or ArduPilot flight stacks and ROS 2 middleware.
Sensors: Good knowledge of high-grade MEMS IMUs, Magnetometers, Barometric Altimeters, and Radar/Optical sensors.
Tools: Experience with simulation environments like Gazebo, AirSim, or custom C++ based 6-DOF simulators.
Preferred Skills
A-PNT: Experience with Assured Position, Navigation, and Timing in degraded environments.
Flight Control Laws: Specific experience with Fixed-Wing dynamics and bank-to-turn control.
Optimization: Experience with trajectory generation and numerical optimization techniques.
Defense/Aero: Prior work on Loitering Munitions, Precision Guided Systems, or BVLOS UAVs.
Personal Attributes
Self-starter with a strong sense of initiative
Collaborative team player who enjoys working in a dynamic environment
Detail-oriented and able to manage multiple projects simultaneously
Passion for drones and unmanned aerial technology
Working Conditions
This is a full-time position based in Bangalore that may require occasional evening or weekend work
May require travel to customer sites or other company locations
Salary And Benefits
Competitive salary based on experience and qualifications
Health insurance
Paid time off and holidays
Opportunities for professional development and growth
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