Software-driven Systems Architect
2 weeks ago
About the Role:
Software System Architect with strong experience in object detection and CMOS/CCD Camera Systems for the architectural design and development of cutting-edge computer vision solutions. The ideal candidate will have strong expertise in AI-based image analysis, deep learning, software quality assurance, and scalable software engineering to drive the development and deployment of systems using advanced imaging technologies.
Key Responsibilities:
•Architect and design AI-based computer vision systems for object detection using CMOS and CCD cameras.
•Develop and optimize deep learning models for real-time image processing and object recognition.
•Define and implement scalable, modular, and high-performance software architectures for AI vision applications.
•Collaborate with cross-functional teams including Systems\hardware engineers, vendors and software developers.
•Evaluate and enhance the performance of image processing pipelines, improving accuracy and reducing false positives.
•Optimize image acquisition and processing techniques for CMOS and CCD sensor technologies.
•Ensure best practices in AI model development, deployment, and security compliance.
•Design and implement robust testing frameworks to validate AI models and image processing algorithms.
•Establish and enforce software quality assurance processes, including code reviews, unit testing, and performance benchmark testing.
•Stay updated with the latest advancements in AI, computer vision, imaging sensor technologies, and software quality standards.
•Provide technical leadership and mentorship to software engineers and AI developers.
Required Skills & Qualifications:
•Bachelor's/Master's Degree Computer Science, Electrical Engineering, AI, or related field.
•5+ years of experience in AI-based computer vision, image processing, and software quality assurance.
•Strong background in deep learning frameworks such as TensorFlow, PyTorch, OpenCV.
•Expertise in FOD detection, object detection, and segmentation techniques.
•Proficiency in programming languages such as Python \QT Framework \C#
•Hands-on experience with CMOS and CCD camera technologies for image acquisition.
•In-depth knowledge of traditional image processing techniques and feature extraction methods.
•Strong understanding of software testing methodologies, including functional, performance, and regression testing.
•Experience with automated testing tools and frameworks for AI and image processing applications.
Deep learning
Machine Learning
Signal and Image Processing
Pipelines
Design Patterns
Architect
Artificial Intelligence
Software Engineering
Azure Machine Learning
Agile
Architectural Design
PyTorch
Technical Leadership
C#
C++
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