Advanced Embedded System Specialist

2 weeks ago

Bengaluru, Karnataka, India beBeeEmbedded Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Embedded Linux Developer Position

We are seeking a highly skilled Embedded Linux Developer with 12 years of hands-on experience in firmware and embedded software development. This role involves working on AI-powered CCTV surveillance solutions, focusing on camera firmware, SDK integration, secure boot, and AI model deployment on embedded platforms.

Key Responsibilities:

  • Develop and integrate firmware/software on ARM/RISC-V based SoCs (e.g., InnoFusion, Realtek, Sigmastar).
  • Port and optimize AI models (YOLO, MobileNet, CNNs) for NPUs/edge inference.
  • Implement secure boot, OTA updates, and encryption (RSA, AES, OTP).
  • Work with camera ISP drivers, video pipelines, H.264/H.265 codecs, and RTSP/ONVIF streaming.
  • Build AI features such as motion detection, object tracking, fire/smoke detection.
  • Interface with camera sensors, storage (eMMC/SD), Wi-Fi/Ethernet/4G modules.
  • Debug and troubleshoot hardware/software issues using GDB, JTAG, oscilloscopes, serial consoles.
  • Collaborate with hardware and cloud teams for device provisioning and management.

Required Skills and Qualifications:

  • Bachelors/Masters degree in Electronics, Computer Engineering, or Embedded Systems.
  • 1 - 2 years of experience in Embedded Linux development.
  • Strong in C/C++, Embedded Linux, U-Boot, Yocto/Buildroot.
  • Basic understanding of AI frameworks (TensorFlow Lite, ONNX, or vendor SDKs).
  • Experience in communication protocol/interfaces like uart, fuart, spi, i2c, tcp-ip, udp etc.
  • Exposure of video pipeline and camera interfaces (MIPI CSI, ISP).
  • Exposure to secure boot and key provisioning concepts.
  • Experience in debugging embedded systems with industry-standard tools.

Preferred Skills:

  • Exposure to AI/vision SoCs like InnoFusion C5-36GW, Realtek, Augentix, Sigmastar, Mediatek, Nvidia etc.
  • Hands-on with edge inference engines (Tengine, ncnn, SNPE).
  • Knowledge of Docker, CI/CD, OTA frameworks for embedded.
  • Experience in AI-based video analytics (face recognition, fire/smoke detection).
  • Familiarity with ONVIF, RTSP streaming protocols.

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