GNC Engineer

GNC Engineer

Full-Time | Core Team

LAT Aerospace | Perception & Autonomy

At LAT Aerospace, we’re building India’s first clean-sheet hybrid-electric STOL aircraft and a next-generation autonomy stack powering aircraft for complex missions. Our team is kicking off a new chapter — developing the full flight-control, obstacle-avoidance, GNSS-denied navigation, and swarm-coordination layers that will define LAT’s autonomy architecture. If you’re excited by hard problems — sub-meter localization without GPS, robust control in unstructured environments, and scalable multi-agent coordination — this is where you build it.

What you’ll do?

• Design and implement core flight-control laws (attitude, position, trajectory control) for fixed-wing and VTOL UAVs operating in dynamic environments.
• Develop onboard obstacle-avoidance algorithms using camera, lidar, and IMU data to support high-speed, low-altitude flight.
• Build GNSS-denied navigation pipelines including terrain-relative navigation, visual-inertial odometry (VIO), map matching, and sensor fusion for sub-meter localization.
• Write swarm guidance and coordination algorithms for multi-vehicle behaviors: task allocation, formation control, collision avoidance, and decentralized decision-making.
• Own end-to-end GNC simulation workflows — from 6-DOF simulation to HIL/SIL testing, validation, and real-world flight experiments.
• Collaborate with the perception, autonomy, and mission-control teams to integrate control logic with real-time sensing, planning, and compute constraints.
• Tune, test, and flight-validate algorithms on test UAVs; iterate rapidly based on field data.
• Build clean, modular, well-documented control software ready for scaling into LAT’s larger aircraft programs.

What we're looking for?

• Strong foundation in classical and modern control theory, nonlinear dynamics, state estimation, and filtering.
• Hands-on experience writing flight-control algorithms for UAVs (PX4, ArduPilot, custom FCS, or proprietary stacks).
• Proficiency in MATLAB/Simulink, Python, and/or C++ for control development and simulation.
• Experience with sensor fusion (EKF, UKF, complementary filters) and handling real-world sensor noise, delay, and drift.
• Familiarity with VIO, SLAM, terrain-relative navigation, or perception-aided localization.
• Exposure to multi-agent control, swarm behaviors, or distributed systems is a strong plus.
• Comfort working with 6-DOF simulators, HIL setups, Gazebo/ROS/PX4, or custom simulation environments.
• Ability to move fast, test fast, and iterate based on flight data.

Why LAT?

• Core-team role building the autonomy brain of India’s most ambitious aerospace startup.
• Ownership, speed, and the opportunity to define a new class of systems from scratch.