Job Summary :

We are looking for a Computer Vision Robotics Engineer with strong hands-on experience in developing and integrating computer vision solutions for robotic applications.

The role will focus on building vision-based software, developing image-processing and AI models, integrating perception modules with robotic systems, and optimizing solutions for real-time applications.

Key Responsibilities :

- Develop and implement computer vision algorithms for robotic applications.

- Build solutions for object detection, image classification, object recognition, tracking, and segmentation.

- Develop image-processing pipelines using OpenCV and related computer vision libraries.

- Work with camera and sensor data to develop reliable perception solutions.

- Develop and integrate computer vision modules with robotic software systems.

- Work with ROS/ROS2 to integrate perception components into robotics applications.

- Develop and deploy machine learning and deep learning models for vision-based use cases.

- Train, test, evaluate, and optimize computer vision models based on application requirements.

- Optimize vision algorithms for real-time performance and efficient resource utilization.

- Develop APIs and software components for integrating computer vision capabilities with other applications.

- Debug and resolve issues related to image processing, model inference, application performance, and robotics integration.

- Conduct testing and validation of computer vision solutions in development and production environments.

- Collaborate with robotics, software, AI/ML, and embedded engineering teams.

- Maintain technical documentation related to algorithms, implementations, testing, and deployments.

- Participate in proof-of-concepts and development of new computer vision capabilities.

Required Skills :

- 6 - 8 years of experience in Computer Vision, Robotics Software, AI/ML, or related areas.

- Strong programming skills in Python and/or C++.

- Hands-on experience with OpenCV and computer vision libraries.

- Strong understanding of image processing and computer vision fundamentals.

- Experience with object detection, classification, tracking, and segmentation.

- Experience with deep learning frameworks such as PyTorch or TensorFlow.

- Experience developing and deploying ML/CV models in real-world applications.

- Working knowledge of ROS/ROS2.

- Experience working with camera-based systems and image/video data.

- Understanding of model optimization and real-time inference.

- Good knowledge of Git, Linux, debugging, and software development practices.

- Strong problem-solving and analytical skills.

- Good understanding of software development lifecycle and testing practices.