Lead AI Computer Vision Architect
2 weeks ago
- Key Responsibilities:
- Design and develop AI computer vision applications using industrial data captured from fixed cameras or drones.
- Analyze images for anomaly detection in complex industrial settings such as power plants, refineries, and petrochemical facilities.
- Select and implement classified image libraries and algorithms for developing anomaly detection applications.
- Program automated detection applications to analyze industrial data.
- Develop expertise in various imaging formats used in industrial settings.
- Support the installation and running of product demonstrations.
- Test and refine algorithms for analyzing videos and improving detection sensitivity.
- Evaluate and recommend state-of-the-art computer vision algorithms for specific applications.
- Develop automated applications for routine inspections using drones.
- Port, implement, and optimize analytics and machine learning algorithms using special purpose computing architectures.
- Provide secondary support and bug fixing for active applications at client sites.
- Contribute to expanding and sustaining the company knowledge base through training and mentoring.
- Establish technical performance benchmarks.
- Support the sales team with technical clarifications during the bidding process.
- Assist the project team with estimates, schedules, and resource loading.
- Develop solution architectures and generate drafts for design reviews.
- Help develop project documentation and client training materials.
- Technical Skills & Experience:
- 10+ years of experience in building computer vision applications using AI.
- Hands-on experience with Python, C++ scripting languages, and industrial computer vision applications using AI.
- Strong project experience in developing computer vision applications using OpenCV, TensorFlow, and Keras.
- Experience in industrial automation use cases using computer vision AI.
- Desirable: Certification in AI / Data Analytics / Deep Learning, personal Github account, and experience in real-time video analytics pipeline.
- Process or Power industry experience is a plus.
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