Lead Computer Vision Engineer

Job Summary:
As our Lead Computer Vision Engineer, you'll architect and implement advanced vision systems that enable our robots to perceive, understand, and interact with physical environments. You'll work on cutting-edge challenges in quality inspection, defect detection, and visual-guided manipulation, directly impacting our product's core capabilities.

Key Responsibilities:

• Design and optimize computer vision systems tailored for physical environments
• Develop the defect detection and localization algorithms for quality control
• Implement reinforcement learning based algorithm for surface quality correction system
• Implement and refine object detection, localisation, segmentation algorithms
• Build and maintain simulation environments for testing and validating vision systems
• Build train datasets and pipeline for vision model training
• Collaborate with cross-functional teams to integrate vision systems into robotic platforms

Qualifications and Skills:

• Bachelor's/Master's (MS or PhD) in Computer Science, Computer Vision, AI, ML, or related field
• 5-10 years of experience in Computer Vision and AI
• Expertise in image processing, including distortion correction, color correction, and 2D to 3D vision
• Strong knowledge of deep learning frameworks like TensorFlow and PyTorch for computer vision
• Experience in object detection, segmentation, and surface inspection techniques preferred
• Experience with simulation tools such as NVIDIA Isaac Sim and AI Habitat
• Excellent programming skills in Python and other relevant languages

Why Join Us:

• Join a dynamic startup and work directly with the founders to shape the future of AI & Robotics
• Be part of a mission to create intelligent robots that eliminate the need for human labour in harsh and unsafe environments
• Join a team that values open feedback, encourages wild ideas, and keeps hierarchy out of brainstorming
• Experience the thrill of building not just a product, but a company from the ground up

To apply, please send your resume and a brief description of your relevant experience to [email protected].