[Hiring] Camera BSP Engineer @Jabil

Role Description

We are looking for a Camera BSP & Middleware Engineer to drive the design and development of a unified camera infrastructure across Linux and Android platforms. This role combines deep embedded Linux and Android expertise with camera subsystem integration. The engineer will be responsible for:

• Sensor bring-up
• Driver development
• Middleware integration
• Image quality tuning

Ensuring compliance with Android Camera HAL standards and optimized multimedia performance across platforms.

Qualifications

• Strong experience with Linux kernel camera drivers and V4L2 (including sub-device drivers)
• Proven experience integrating and maintaining Android Camera HAL
• Hands-on experience with camera sensor bring-up and board-level integration
• Experience working with Device Tree / DTBO overlays, including power sequencing, reset, and clock (MCLK) configuration
• Experience tuning image quality pipelines, including:
  • 3A algorithms (AE, AWB, AF)
  • Lens Shading Correction (LSC)
  • Temporal Noise Reduction (TNR)
• Ability to debug complex camera pipelines across kernel and user space
• Experience with Git/Gerrit and build systems (Yocto and AOSP)
• Strong understanding of embedded Linux and Android system architecture

Requirements

• Own cross-platform (Linux and Android) camera architecture and board bring-up
• Develop and maintain Linux camera drivers (V4L2 sub-devices)
• Integrate and support Android Camera HAL components
• Create and validate Device Tree / DTBO overlays for camera hardware configuration
• Automate media graph validation, streaming tests, and long-running stress test suites
• Tune image processing pipelines using vendor-provided IQ tools
• Collaborate closely with hardware teams on CSI timing, PHY configuration, and sensor onboarding
• Support performance optimization and long-term platform stability

Preferred Skills

• Experience with ISP pipelines and proprietary HAL implementations
• Knowledge of multimedia frameworks such as GStreamer or OpenCV
• Experience working with high-resolution or multi-camera systems
• Familiarity with automated validation frameworks for camera subsystems