Job Description

Responsibilities

• End-to-End Project Ownership: Take comprehensive responsibility for development of computer vision pipelines, from initial concept to deployment including ideating, building and refining the solutions.
• High-Performance Pipelines: Spearhead the development of robust and scalable computer vision pipelines focusing on both local and cloud-based applications.
• Benchmarking and Working with State-of-the-Art Models: Engage in thorough benchmarking activities to assess and enhance the accuracy of latest computer vision breakthroughs. Strive for optimization and latest advancements in the field.
• Bug Fixing: Proactively identify and resolve software bugs, ensuring the deployment process is smooth and efficient.
• Cross-Team Collaboration for Solution Development: Engage in close collaboration with various stakeholders, including subject matter experts, to develop comprehensive solutions.

• Bachelor\'s or master\'s in computer science, Electrical Engineering, or related field, or equivalent experience.
• Over 3 years of experience working with Computer Vision, especially in training models and developing efficient pipelines, with a focus on object detection, image segmentation, and pose estimation.
• Proficiency with Python, image processing libraries like OpenCV and Pillow and deep learning frameworks like PyTorch and TensorFlow.
• Demonstrated expertise in developing and implementing computer vision pipelines, understanding visual data processing and algorithms.
• Solid understanding of data structures, algorithms, and software design principles.
• Experience in model optimization, including edge hardware deployment. Experience with Deepstream/GStreamer/Edge optimised libraries is a plus.
• Research experience or working experience with loT/Edge devices .
• Demonstrated ability to produce highly scalable pipelines, working effectively both independently and as part of a team.
• Excellent communication abilities to articulate findings and technical challenges to both technical and non-technical stakeholders.

Manpower