Computer Vision Engineer

Joining Gadgeon offers a dynamic and rewarding career experience that fosters both personal and professional growth. Our collaborative culture encourages innovation, empowering team members to contribute their ideas and expertise to cutting-edge projects. We are currently looking for a Computer Vision Engineer to join our team. The ideal candidate should have 3-4 years of experience and possess a strong background in image processing, deep learning, and machine learning techniques. Hands-on experience in developing and deploying computer vision applications is also required. As a Computer Vision Engineer at Gadgeon, your responsibilities will include: - Designing, developing, and optimizing computer vision algorithms for tasks such as object detection, tracking, segmentation, depth estimation, and activity recognition. - Implementing and training deep learning models using frameworks such as TensorFlow, PyTorch, and OpenCV. - Processing and analyzing large-scale image and video datasets to extract meaningful insights. - Developing and optimizing deep learning pipelines, including dataset preparation, model training, evaluation, and deployment. - Working with multiple camera inputs and multimodal data for real-time applications. - Collaborating with software engineers and data scientists to integrate computer vision models into production environments. - Researching and implementing the latest advancements in computer vision and deep learning. - Debugging and troubleshooting issues in vision-based applications, optimizing for accuracy and performance. - Working on AI infrastructure, machine learning accelerators, and on-device optimization. Required Qualifications: - B.Tech in Computer Science, Electrical Engineering, Electronics, or a related field. - Hands-on experience developing learning algorithms for computer vision tasks such as object detection, object tracking, segmentation, optical flow, and multi-view geometry. - Strong understanding of deep learning architectures, representational learning, and domain adaptation. - Ability to train, debug, and deploy deep learning models, iterating on failure characterization and model improvement. - Proficiency in Python and ML/DL frameworks such as TensorFlow, PyTorch, and TensorRT. - Experience working with multiple input sources such as cameras, LiDAR, and embedded controllers. - Hands-on experience with MLOps tools and methods is a plus. - Familiarity with AI infrastructure, machine learning accelerators, and on-device optimization. - Strong programming skills with experience in C++, Python, or C#. - Experience with version control tools such as Git and development in Linux environments. - Highly motivated individual with a strong work ethic, the ability to work independently, and adaptability to a fast-paced environment. Preferred Qualifications: - Experience in 3D computer vision, SLAM, or LiDAR processing. - Knowledge of adversarial and generative models. - Exposure to hardware acceleration and embedded AI deployment. - Strong understanding of software development best practices and performance optimization.,