Project description

Our client, a leading manufacturer of high-end household appliances, is expanding into new smart product lines. As part of this strategic initiative, a large-scale global program is being implemented across the company's IP portfolio. This includes the development of new embedded software, enhancements to cloud infrastructure.

Responsibilities

• Work directly with computer vision perception engineers, and camera ISP engineers.
• Define the image quality requirements for customer use cases.
• Develop image processing algorithms to optimize camera image quality for performance improvement of computer vision applications.
• Develop custom ML models for visual recognition and train them from scratch.
• Quantization and pruning of ML models.
• Data evaluation using relevant metrics to increase model performance.
• Implement computer vision/image processing algorithms in fast/optimal C++ code.
• Implement heuristic/math algorithms and probabilistic methods for camera AI.
• Research existing C++ solutions for CV logic.
• Develop cross platform C++ code.
• Cover algorithms and CV code with unit tests.
• Ramp up on new technologies related to CV/ML/algorithms (not R&D).
• Integrate machine learning modules into algorithms.

Qualifications

Must have

• Bachelor's Degree or higher in Computer Science, Software Engineering, or a related field.
• 3-5 years of experience developing computer vision applications/algorithms.
• Participation in at least 2 image processing / computer vision projects and 1 productized.
• Image processing / computer vision background/understanding.
• Strong C/C++ experience.
• Experience with OpenCV and ML frameworks such as PyTorch, TensorFlow, TensorFlow Lite.
• Deep understanding of neural network architectures.
• Experience working with embedded devices in C++ on Linux.
• Solid understanding of 2D/3D geometry and algebra.
• Desire to learn new technologies.
• Desire to follow test-driven development (in CV/ML too).

Nice to have

• Experience with machine learning integration, inference engines.
• Machine learning general understanding.
• Experience building for Android/Yocto.
• OpenCL/CUDA or OpenGL/Vulkan (shaders) experience/understanding and willingness to learn or any other SIMD language.