VTOL Aviation India Pvt. Ltd. is a defence-grade UAV and advanced aerial systems manufacturer, specializing in indigenous unmanned platforms, electro-optical payloads, onboard cameras, AI-enabled subsystems, and mission-critical in-house software. We build next-generation UAVs for surveillance, mapping, tactical operations, and autonomous missions aligned with Make in India and future-ready military requirements.
We are expanding our perception and autonomy engineering team to strengthen UAV navigation, vision intelligence, and real-time onboard processing.
Key Responsibilities
- Deploy and optimize AI/ML computer vision models on edge compute platforms such as NVIDIA Jetson (Nano/Xavier/Orin), Hailo, and other AI accelerators.
- Build and accelerate perception, mapping, and sensor-fusion pipelines using CUDA, TensorRT, GPU frameworks, and real-time optimizations for UAV flight environments.
- Develop, integrate, and fine-tune Visual Odometry (VO) and SLAM algorithms for autonomous navigation and GPS-denied operations.
- Work with various camera systems, including mono, stereo, gimbal-mounted EO sensors, and high-speed image pipelines used in UAV payloads.
- Collaborate with hardware, flight-control, and autonomy teams to ensure seamless integration of perception modules with UAV avionics.
- Manage real-time networking, data streaming, and low-latency communication between onboard compute and ground control systems.
- Perform system-level testing, tuning, and verification on actual UAV platforms.
- Contribute to in-house development of perception, mapping, and autonomy subsystems, aligned with VTOL's product roadmap.
Technical Skills
- Strong proficiency in GPU programming CUDA, TensorRT, OpenCL, or similar frameworks.
- Hands-on experience in deploying AI/ML vision models on edge hardware (Jetson/Orin/Hailo/Coral).
- Practical experience with VO/SLAM frameworks such as ORB-SLAM, VINS-Fusion, RTAB-Map, OKVIS, etc.
- Solid command over Python & C++ for robotics and high-performance computing.
- Strong understanding of computer vision algorithms, camera calibration, multi-camera setups, and EO payload workflows.
- Experience with real-time communication protocols, data streaming, and onboard-to-ground data links.
- Basic working knowledge of ROS/ROS2, sensor drivers, and robotic middleware.
Educational Background
- Bachelor's/Master's degree in Robotics, Computer Engineering, Computer Vision, Electronics, or related disciplines.
- Experience of 2-3 years preferred.
Interested candidates may email their resume with cover letter and details of existing CTC, expected CTC and notice period to [Confidential Information]
