Computer Vision / Artificial Intelligence / Machine Learning

We are looking for Senior Computer Vision Engineers for Contractual/Freelancing Roles. The job description and requirements are as following:

Key Responsibilities:
Algorithm Development: Design, develop, and optimize computer vision algorithms for image processing, object detection, recognition, and segmentation.
Model Training: Develop and train machine learning models tailored for image analysis and visual data interpretation.
AI Integration: Implement and integrate AI models into existing software and hardware systems, ensuring high performance and scalability.
Data Analysis: Analyze and process large datasets of images and video feeds to identify patterns, trends, and insights.
Performance Optimization: Optimize algorithms and models for real-time processing and ensure they can handle large-scale data efficiently.

Required Technical Qualifications:
Experience: Minimum of 2 years of professional experience in computer vision, with a proven track record of working on complex image processing and ML projects.
Programming Skills: Proficient in programming languages such as Python, C++, and MATLAB. Experience with deep learning frameworks like TensorFlow, PyTorch, or Keras.
Algorithm Expertise: Strong understanding of computer vision algorithms and techniques, including but not limited to convolutional neural networks (CNNs), object detection (e.g., YOLO, Faster R-CNN), image segmentation (e.g., U-Net), and feature extraction.
AI/ML Knowledge: In-depth knowledge of machine learning principles and experience with supervised, unsupervised, and reinforcement learning.
Data Handling: Experience in handling and processing large datasets, including image and video data. Familiarity with data augmentation techniques and synthetic data generation.
Performance Tuning: Expertise in optimizing models for deployment in real-time systems and experience with GPU acceleration (e.g., CUDA, TensorRT).
Tools & Libraries: Proficiency with OpenCV, scikit-image, and other relevant libraries. Experience with version control systems like Git.
Analytical Skills: Strong analytical and problem-solving skills with the ability to think creatively and develop innovative solutions.
Communication: Excellent written and verbal communication skills, with the ability to present complex technical information to non-technical stakeholders.