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Job Description

Key Responsibilities :

- Basic understanding of ISP pipeline modules

- Develop and maintain HAL (Hardware Abstraction Layer) and KMD (Kernel Mode Driver) interfaces interacting between host and camera sub-modules.

- Understand tuning parameters, and system teams to evolve tuning parameters and optimization strategies for image quality and performance.

- Manage memory and buffer lifecycles, implementing efficient buffer queue mechanisms under Linux kernel constraints.

- Understand image quality (IQ) tuning tools, scripts (Python/C++/MATLAB), and automation frameworks.

- Thrrough knowledge of IFE( Image Front end) and IQ ( Image Quality).

- C++ design patterns is must and good at Linux Kernel Programming.

- Benchmark and validate image output quality using objective metrics (e.g. MTF, noise, low-light performance) via IQ test charts and automation script.

- Participate in debugging, profiling, and performance optimizations, ensuring low power, latency, and resource usage.

- Author and maintain technical documentation : API specs, tuning guides, interface descriptions, and test plan.

Qualifications & Skills : (Minimum Requirements)

- Bachelors degree or higher in Computer Science, Electrical/Electronic Engineering, Imaging Science, or related fieldGoogle

- 2+ years experience in C/C++ software development; exposure to embedded systems or Linux driver development

- Strong knowledge of ISP fundamentals, digital image processing, and camera tuning concepts (AWB, AE, 3A)Reddit+4Google+4The Muse+4

- Familiar with memory/buffer management in Linux or embedded environments

- Experience in writing automation/test scripts using Python, MATLAB, or similar

Preferred Skills :

- Masters or PhD in relevant technical field

- 4+ years in consumer camera ISP software development or tuning

- Knowledge of color science, imaging sensor characteristics (CMOS/Bayer), IQ metrics like MTF, FOV,

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- Familiarity with hardware drivers, HAL design, debugging tools, profiling, Linux kernel fundamentals

- Experience in automated IQ testing frameworks, camera sensor integration and validation pipelines

- Exposure to ML-based image processing or algorithm development

- Prior exposure to HAL interfaces, buffer management, and tuning interfaces.


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