We are seeking a highly skilled Computer Vision Engineer to develop, optimize, and deploy AI-driven image and video analysis solutions. You will be responsible for designing deep learning models, improving object detection algorithms, and integrating computer vision applications into real-world products. This role requires expertise in image processing, neural networks, and deploying AI models in production environments.

Key Responsibilities:

• Develop and optimize computer vision algorithms for tasks such as object detection, image segmentation, and facial recognition.
• Train and fine-tune deep learning models using frameworks like TensorFlow, PyTorch, or OpenCV.
• Design and implement efficient data pipelines for preprocessing and augmenting image and video datasets.
• Deploy computer vision models into production environments, ensuring scalability and real-time processing capabilities.
• Collaborate with software engineers to integrate AI solutions into applications, robotics, and automation systems.
• Conduct research and stay updated with the latest advancements in computer vision and AI.
• Perform model evaluation, A/B testing, and performance tuning to improve accuracy and efficiency.
• Ensure ethical AI practices and compliance with data privacy regulations.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Strong proficiency in Python, C++, or other relevant programming languages.
• Hands-on experience with computer vision libraries such as OpenCV, Dlib, or FastAI.
• Expertise in deep learning architectures like CNNs, RNNs, and GANs.
• Familiarity with cloud platforms (AWS, Azure, GCP) and edge computing for AI deployment.
• Experience with real-time image/video processing and optimization techniques.
• Strong analytical and problem-solving skills.
• Excellent teamwork and communication skills.

Preferred Qualifications:

• Experience working with LiDAR, 3D vision, or augmented reality (AR) applications.
• Knowledge of reinforcement learning for vision-based robotics.
• Previous experience in industries such as healthcare, autonomous vehicles, or security surveillance.