Computer Vision Engineer

Company Description TARDID Technologies is a deep-tech AI company focused on building physics-driven intelligence for mission-critical industries where failure is not an option. Using its proprietary BrainBox platform, TARDID delivers solutions across defence, maritime, railways, and industrial sectors, including autonomous surveillance, networked warfare management, railway collision avoidance, smart port operations, and India’s first AI-optimised Electric Outboard Motor. The company is recognised by Gartner as a leading technology provider and is trusted by the Indian Navy and Indian Army. TARDID’s technology is built on 100% indigenous intellectual property and includes nine world-first innovations. The organization is ISO 9001:2015 and ZED Certified, reflecting strong quality and operational standards.

Role OverviewWe are seeking a motivated Computer Vision Engineer to join our team. The selected candidate will contribute to the development of vision-based perception systems for perimeter surveillance and warfare management platforms. This role offers an opportunity to work on real-world AI applications involving object detection, tracking, situational awareness and sensor fusion.

Responsibilities· Assist in developing and improving computer vision and deep learning models.

• Work on image and video processing pipelines from electro-optical, infrared, and other imaging sensors.
• Support data collection, annotation, preprocessing, and dataset management activities.
• Implement and evaluate object detection, classification, segmentation, and tracking algorithms.
• Participate in model training, validation, and performance benchmarking.
• Collaborate with software, robotics, navigation, and systems engineering teams.
• Contribute to deployment and optimization of AI models on edge devices and embedded platforms.
• Document experiments, technical findings, and development activities.

Required Qualifications· Bachelor's or Master's degree in Computer Science, Electronics, AI/ML, Robotics, or a related field.

• Strong understanding of Python programming.
• Familiarity with OpenCV and basic image processing techniques.
• Knowledge of machine learning and deep learning fundamentals.
• Exposure to frameworks such as PyTorch or TensorFlow.
• Understanding of computer vision concepts such as:

o Object Detection

o Image Classification

o Image Segmentation

o Feature Extraction

o Multi-Object Tracking

• Good problem-solving and analytical skills.

Preferred Skills· Experience with YOLO, SSD, Faster R-CNN, or similar detection models.

• Familiarity with Linux development environments.
• Basic understanding of embedded AI deployment.