Computer Vision Engineer

Main Responsibilities Candidates will be performing

• Algorithm Development: Design, implement, and optimize computer vision algorithms for multicamera

surround view monitoring(SVM) systems, the SW includes image enhancement,

transformation and stitching techniques, camera calibration and output rendering.

• Embedded Dev.: Design and develop embedded software for ADAS applications. Implement and

optimize software for automotive ECUs. Integrate the SW with vehicle signals, flash it on hardware.

• Integration & Testing: Integrate software modules with camera drivers and vehicle communication

networks. Conduct rigorous unit, integration, simulation and hardware testing. CAN based hardware

testing, bench top and in vehicle testing and validation is in scope.

• Collaboration: Work cross-functionally with software developers and hardware engineers, system

architects, and application teams to define requirements and troubleshoot complex system-level

issues. Manage SW repositories.

• Mandatory Skills Required (specify keywords)

Note: Profile sourcing and screening will be done based on these keywords

• Keywords: Computer vision, C/C++, Embedded systems, Image processing, Rendering, Renesas, TI,

Linux, ADAS software developer, code optimization, hardware flashing and testing.

• Programming Languages: Intermediate to advance-level proficiency in C and Modern C++ (C++11 or

later) for high-performance application development.

• Platform expertise: Should have worked on ADAS SoCs like, Renesas, TI, NVIDIA, etc. Strong

programming skills in Embedded C/C++. Experience with CAN/I2C/SPI protocols. Should be able to

do SW flashing and testing on HW.

• Computer Vision: Expertise in geometric computer vision, backed by a strong mathematical

foundation in 3D geometry and linear algebra, including fisheye lens modelling, image stitching,

photometric alignment, and conventional feature detection/tracking algorithms. Hands-on

experience or exposure with OpenCV library.

• Graphics & Rendering: Good experience with utilizing graphics APIs (such as OpenGL, OpenGL ES,

or Vulkan) specifically for 3D bowl rendering and dynamic surround-view generation.

• Embedded Systems: Familiarity with embedded operating systems (Linux, QNX, or RTOS) and

understanding of memory management and multi-threading in resource constrained environments.

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