IntelliVision - Computer Vision Engineer - C/C++

2 months ago

Pune, India Intellivision Technologies Private Limited. Full time

Location : Pune

Employment Type : Full Time

Job Description :

As a Computer Vision and AI Engineer, you will play a crucial role in developing and optimizing AI-driven computer vision solutions for embedded systems.

You will work alongside a team of experts to design, implement, and deploy machine learning models across various embedded platforms, ensuring high performance and efficiency.

Key Responsibilities :

- Develop and implement machine learning and deep learning models for video processing and analysis.

- Optimize computer vision models for deployment on embedded systems, including techniques such as pruning, quantization, and architecture-specific optimization.

- Port models to NVIDIA GPUs and various embedded platforms (e., ARM CPUs, NPUs like Ambarella, Sigmastar, Qualcomm) using frameworks such as TensorFlow Lite and other vendor-specific embedded deep learning frameworks.

- Utilize and integrate major deep learning platforms, including TensorFlow, Caffe, and PyTorch, with OpenCV and other computer vision libraries.

- Collaborate with cross-functional teams to address challenges in security, surveillance, and Advanced Driver Assistance Systems (ADAS) applications.

- Write and maintain high-quality code in C/C++ and Python for performance-critical applications.

Required Skills and Experience :

- 2 to 7 years of experience in machine learning and deep learning, especially in the video domain.

- Proficiency with major machine learning frameworks (TensorFlow, PyTorch, Caffe) and computer vision libraries (OpenCV).

- Experience in porting and optimizing models on embedded platforms (e., ARM CPUs, NPUs).

- Strong programming skills in C/C++ and Python, with a focus on performance optimization.

- Familiarity with development in Linux environments and porting C/C++ code for embedded Linux/Android platforms.

- Experience developing solutions for security, surveillance, or ADAS applications, and working with convolutional neural network (CNN) models like YOLO and SSD.

- Understanding of machine learning algorithms, including CNN, RNN, LSTM, SVM, Random Forest, and XGBoost

(ref:hirist.tech)

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