Deep Learning System Architect

hace 2 semanas

Barcelona, Barcelona, España beBee Careers A tiempo completo

Embedded Vision Engineer

We are seeking an experienced Embedded Vision ML Engineer with expertise in TinyML and low-power computer vision to join cutting-edge projects involving gesture recognition and real-time image processing on constrained devices.

The ideal candidate has experience working with ultra-low-power image sensors (e.g., Himax HM01B0) and has deployed lightweight ML models using TensorFlow Lite, QKeras, or Kendryte K210's KPU.

Key Responsibilities:

  • Develop and optimize TinyML-based gesture recognition and low-power computer vision models for embedded devices
  • Work directly with ultra-low-power image sensors such as the Himax HM01B0
  • Deploy and maintain models on embedded platforms using frameworks like TensorFlow Lite, QKeras, or Kendryte K210's KPU
  • Implement quantization-aware training and advanced model compression techniques to maximize efficiency
  • Handle real-time image processing under strict power and performance constraints

Your Background:

  • Proven experience developing vision models on embedded platforms (e.g., microcontrollers, edge AI chips)
  • Strong skills in quantization-aware training, model compression, and deployment of lightweight ML models
  • Comfortable working with ultra-low-power sensors and constrained hardware environments
  • Familiarity with TinyML toolkits and deployment frameworks such as TensorFlow Lite, QKeras, or Kendryte K210 SDK
  • Ability to troubleshoot and optimize embedded vision pipelines for performance and power efficiency

PREFERRED QUALIFICATIONS:

  • Experience with ultra-low-power image sensors and embedded camera hardware
  • Knowledge of real-time embedded system constraints and optimization strategies
  • Contributions to open-source TinyML or embedded vision projects
  • Experience with low-latency computer vision applications on constrained devices

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