About the Role :

We are seeking a skilled Computer Vision Engineer with a strong foundation in deep learning and image processing to join our innovative research and development team. The ideal candidate will be responsible for developing, optimizing, and deploying computer vision models tailored to real-world customer problems, including deployment on edge devices. You will collaborate closely with research teams to transform cutting-edge computer vision algorithms into production-ready solutions.

Key Responsibilities :

- Collaborate with the research team to research, develop, evaluate, and optimize computer vision and deep learning models for diverse real-world applications such as object detection, semantic segmentation, and key-point detection.

- Take end-to-end ownership of computer vision solutions, ensuring they meet customer requirements and performance benchmarks.

- Deploy optimized computer vision models onto edge devices-balancing computational efficiency and accuracy to meet resource constraints.

- Maintain and continuously improve deployed models based on customer feedback and evolving requirements.

- Develop scalable and efficient data handling and machine learning pipelines for model training, validation, and testing.

- Implement algorithms in robust, efficient, and well-tested code, ensuring software quality, maintainability, and performance.

- Design and create platforms for image processing and visualization to support model development and deployment.

- Work closely with cross-functional teams, including software engineers and system integrators, to deliver end-to-end solutions.

Required Skills & Experience :

- Minimum 2 years of hands-on experience in computer vision and deep learning development.

- Strong ability to design and implement deep learning frameworks to solve complex image and video processing problems.

- Proficient in C++ programming with expertise in video analytics.

- Experience with GPU programming and acceleration frameworks such as CUDA.

- Familiarity with NVIDIA DeepStream SDK or similar frameworks for video analytics and edge deployment.

- Practical knowledge of popular computer vision libraries and frameworks such as OpenCV, TensorFlow, PyTorch, Detectron2, or MMDetection.

- Solid understanding of dataflow programming models and pipeline architectures for efficient training and inference.

- Ability to write clean, optimized, and well-documented code, with good software engineering practices.

- Bachelor's degree in Electronics & Telecommunication, Computer Science, IT, Mechanical, or Electronics Engineering.