Vision Systems Architect

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  • Vollzeit
  • 21 Tage her
Project description
  • Owns the end-to-end vision and AI architecture for consumer devices. Defines scalable, power-efficient, and production-ready imaging and perception systems across product lines. Drives technical direction across sensor, ISP, CV, ML, and platform integration.
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.
  • Architect heterogeneous compute utilization (CPU/GPU/NPU/DSP).
  • Define system KPIs: latency, FPS, power, memory, boot time, and robustness.
  • Lead technology selection for inference engines, frameworks, and hardware platforms.
  • Guide SoC bring-up and performance validation for vision pipelines.
  • Establish coding standards, modularization strategy, and long-term maintainability.
  • Identify technical risks early and define mitigation strategies.
  • Collaborate with hardware, ISP, Android/Linux platform, and product teams.
  • Mentor senior engineers and provide architectural governance.
  • Contribute to long-term vision/AI roadmap across product generations.
SKILLSMust have
  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field (PhD preferred).
  • 10-15+ years of experience in imaging/vision/perception systems.
  • Proven experience architecting and shipping multiple consumer products with vision/AI.
  • Deep understanding of imaging pipeline (sensor behavior, ISP, tuning impact).
  • Strong embedded system architecture experience.
  • Expert-level C++ and system-level optimization knowledge.
  • Strong expertise in CV and ML system integration.
  • Experience deploying optimized ML models on consumer SoCs.
  • Experience with heterogeneous compute architectures.
  • Experience defining system-level KPIs and validation strategies.
  • Strong cross-functional leadership and communication skills.
Nice to have
  • Experience with computational photography pipelines. • Experience in AR/VR or advanced camera features. • Experience with silicon bring-up and HW/SW co-design. • Experience with large-scale model deployment and OTA updates. • Experience in multi-camera or depth-sensing systems. • Contributions to patents or technical publications. • Experience leading architecture across multiple product generations.

Luxoft

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