Computer Vision Engineer

Job Description

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 [email protected]