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Vision Systems Architect
Luxoft
Dubai, UAE
Full-time
Mid-Senior
Onsite
Discovered 4 weeks ago
Computer VisionMachine LearningImage ProcessingEmbedded SystemsC++System-Level Optimization
Free
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Computer VisionMachine LearningImage Processing
Role Overview
We are seeking an experienced Vision Systems Architect to lead the design and evolution of next-generation intelligent imaging systems for innovative consumer products.
This role will own the end-to-end vision architecture, spanning image sensing, ISP, computer vision, machine learning, and application integration, while driving performance, image quality, and user experience.
The successful candidate will define scalable AI and vision platforms, optimize deployment on heterogeneous computing architectures, and provide technical leadership across multiple product generations in a highly collaborative, cross-functional environment.
Key Skills for This Role
Computer VisionMachine LearningImage ProcessingEmbedded SystemsC++System-Level Optimization
Full Job Posting
Summary
We are seeking an experienced Vision Systems Architect to lead the design and evolution of next-generation intelligent imaging systems for innovative consumer products.
This role will own the end-to-end vision architecture, spanning image sensing, ISP, computer vision, machine learning, and application integration, while driving performance, image quality, and user experience.
The successful candidate will define scalable AI and vision platforms, optimize deployment on heterogeneous computing architectures, and provide technical leadership across multiple product generations in a highly collaborative, cross-functional environment.
Responsibilities
- Define and own end-to-end vision system architecture (sensor → ISP → CV/ML → application layer).
- Translate product and UX requirements into scalable technical solutions.
- Define image quality strategy aligned with AI and user experience goals.
- Architect reusable, modular CV/ML frameworks across multiple product SKUs.
- Drive system-level trade-offs across performance, power, cost, and thermal limits.
- Define AI model lifecycle strategy from training to OTA deployment.
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