Computer Vision System Engineer - Image Signal Processing

Computer Vision Systems (Algorithm) Engineer

Job Description :

Successful candidates will be part of a systems and R&D team that develops embedded camera and imaging solutions, image signal processor (ISP), video codec hardware as well as advanced algorithms for computer vision and image / video processing.

Responsibilities :

The job responsibilities may include a subset of the following :

• Develop and / or optimize depth estimation and optical flow algorithms, enabling critical use-cases across mobile, AR / VR and automotive platforms
• Research and develop power-efficient computer vision algorithms, deep learning architectures and models in computer vision for AI-enabled camera, video, AR / VR products
• Developing or Optimizing image processing and computer vision algorithms for HW acceleration
• Support product teams for commercialization, such as solution optimization, performance profiling and benchmarking.
• Proficiency in programming languages such as Python (NumPy, OpenCV, TensorFlow, PyTorch) for developing computer vision algorithms and applications. Knowledge in C++ is a plus.
• Strong understanding of computer vision fundamentals including image processing techniques (filtering, morphological operations), feature extraction (SIFT, HOG, Optical Flow), object detection (YOLO, SSD, R-CNN), segmentation (U-Net, Mask R-CNN), and tracking.
• Experience with deep learning frameworks such as TensorFlow, PyTorch, Keras, and OpenCV for developing and deploying deep neural networks for computer vision tasks.
• Knowledge of popular deep learning architectures for computer vision such as CNNs, RNNs, GANs, & Transformer models.
• Strong mathematical foundations including linear algebra, calculus, probability theory, and optimization techniques (e.g., gradient descent, Adam optimizer) used in ML algorithms.
• Prior exposure to cloud platforms (preferably AWS) to deploy data pipelines and to use tools / services like AWS SageMaker, Kinesis, MLFlow etc.
• Exposure to Generative AI algorithms for Computer Vision like Stable Diffusion is a plus.
• Experience with GPU programming and optimization using CUDA or OpenCL for accelerating deep learning computations is a huge plus.
• Proficient in using computer vision libraries and tools for feature extraction, image registration and object recognition.

Required qualifications :

(ref : hirist.tech)