Role Objective
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
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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.
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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.
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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.
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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.
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Path Planning & Trajectory Optimization: Implement algorithms for long-range energy-efficient routing, obstacle avoidance, and dynamic re-tasking in complex 3D environments.
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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:
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Bachelor’s or Master’s (PhD preferred) in Aerospace Engineering, Robotics, or a related field with a focus on Control Theory.
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3–5+ years in GNC engineering, specifically working on autonomous aircraft, missiles, or high-speed UAVs.
Skills and Abilities:
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Control Theory: Expert knowledge of Classical (PID, Root Locus) and Modern (LQR/LQG, Robust Control, MPC) control systems.
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Mathematics: Deep understanding of Linear Algebra, Quaternion math, Coordinate Transformations, and vehicle dynamics.
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Software: Proficiency in C++ (for real-time deployment) and MATLAB/Simulink (for modeling and filter design). Experience with Python for data analysis.
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Ecosystems: Familiarity with the PX4 or ArduPilot flight stacks and ROS 2 middleware.
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Sensors: Good knowledge of high-grade MEMS IMUs, Magnetometers, Barometric Altimeters, and Radar/Optical sensors.
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Tools: Experience with simulation environments like Gazebo, AirSim, or custom C++ based 6-DOF simulators.
Preferred Skills:
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A-PNT: Experience with Assured Position, Navigation, and Timing in degraded environments.
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Flight Control Laws: Specific experience with Fixed-Wing dynamics and bank-to-turn control.
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Optimization: Experience with trajectory generation and numerical optimization techniques.
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Defense/Aero: Prior work on Loitering Munitions, Precision Guided Systems, or BVLOS UAVs.
Personal Attributes:
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Self-starter with a strong sense of initiative
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Collaborative team player who enjoys working in a dynamic environment
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Detail-oriented and able to manage multiple projects simultaneously
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Passion for drones and unmanned aerial technology
Working Conditions:
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This is a full-time position based in Bangalore that may require occasional evening or weekend work
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May require travel to customer sites or other company locations
Salary and Benefits:
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Competitive salary based on experience and qualifications
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Health insurance
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Paid time off and holidays
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Opportunities for professional development and growth
