Embedded Software Engineer

We are seeking a skilled and experienced Embedded Software Engineer to join our team, focusing specifically on the development and optimization of camera functionality for our embedded devices running on Android. This role will involve working deeply with Quectel smart modules and their underlying platforms, developing and integrating camera drivers, implementing image processing pipelines and ensuring high-quality camera performance tailored to specific application needs.

Responsibilities:

• Design, develop and integrate kernel and user space camera drivers for various components including image sensors, autofocus (AF) actuators, EEPROMs and LED flashes.
  
• Configure camera-related hardware interfaces, manage GPIOs for control and set up power supplies and power-on/off sequences within the kernel device tree.
  
• Implement and configure user space driver parameters, defining sensor output formats (like RAW or YUV), connection modes (such as MIPI CSI), resolutions, frame rates and MIPI CSI lane configurations.
  
• Integrate and configure camera tuning data, including chromatix code for Bayer sensors or handle specific configurations required for YUV sensors. 
  
• Troubleshoot and debug camera bring-up failures, image quality issues and performance bottlenecks by analyzing kernel logs and system behavior, looking for errors like SOF freeze, ERROR_CRC and ERROR_PHY_DL0_FIFO_OVERFLOW.
  
• Work on the Android Board Support Package (BSP), focusing on the Camera Hardware Abstraction Layer (HAL) to provide a consistent programming interface for applications.
  
• Utilize standard Android SDK Camera APIs for developing camera-based applications.
  
• Collaborate closely with hardware engineers during the component selection phase (image sensors, lenses, processors, etc.) and contribute to the overall embedded camera system design.
  
• Perform camera tuning processes to fine-tune hardware and software parameters, achieving optimal performance and image quality for specific applications by adjusting settings like Autofocus (AF), Auto Exposure (AE) and Auto White Balance (AWB). 
  
• Explore and integrate AI/ML algorithms for advanced vision functionalities such as object detection, facial recognition or predictive analytics. For example, use of AI and machine learning with Quectel modules for road hazard detection.
  
• Ensure thermal management considerations are adequately addressed in software design to maintain system efficiency and reliability, especially in demanding operating environments.
  
• Implement and execute effective testing procedures under various lighting conditions and scenarios to ensure product reliability and consistent performance.
  
• Leverage Hardware Abstraction Layers (HALs) to enhance the flexibility, scalability and future-proofing of camera designs.
  

Requirements

Mandatory

• Proven experience in embedded software development, with a strong focus on camera systems and Android platforms.
  
• Proficiency in C/C++ programming is essential for interacting with system APIs and low-level hardware.
  
• Experience with Android BSP and HAL development, specifically the camera HAL, is a key requirement.
  
• Familiarity with camera driver development models in both the kernel and user space on Linux/Android systems.
  
• Hands-on experience working with camera interfaces such as MIPI CSI.
  
• Practical experience in bringing up and configuring camera sensors, including understanding I2C communication, power sequencing and timing.
  
• Experience in debugging complex embedded camera systems, including log analysis for hardware and software issues.
  

Secondary Skills:

• Experience working with Qualcomm multimedia and camera frameworks is highly desirable.
  
• Knowledge of image processing concepts and algorithms, including 3A algorithms (AF, AE, AWB), noise reduction and color correction.
  
• Experience with specific Quectel smart module series (e.g., SC600Y/T, SC200E/V, SA800U, SG865W). 
  
• Experience working with Quectel smart modules and Qualcomm processors used in embedded devices is a significant advantage.
  
• Understanding of performance optimization techniques for real-time image processing and video streaming.
  
• Experience integrating and optimizing AI/ML algorithms within embedded vision systems.
  
• Knowledge of relevant communication protocols for camera systems.
  
• Experience with camera tuning tools, labs and methodologies.
  
• Contribution to open-source projects like LineageOS or Google AOSP.
  

Benefits

Comprehensive Employee Benefits

• Health & Wellness (Life and health insurance) 
  
• Enrollment Option for National Pension Scheme 
  
• Flexible Work Arrangements when in need 
  
• Generous Leave Policy 
  
• Team Off-sites & Social Events 
  
• Performance Bonuses
  

In addition to a competitive and attractive pay & benefits packages, we provide career development that align with the strategic objectives and the employee needs.

I'm interested