Remote Computer Vision Engineer (The Visionary Technologist)

Description:

• The Computer Vision Engineer will design, implement, and optimize computer vision systems for transformative applications across various industries.
• This role involves developing innovative algorithms and models that enable computers to process and interpret images and videos.
• Key responsibilities include developing computer vision algorithms for tasks such as object detection, facial recognition, image segmentation, and motion tracking using frameworks like OpenCV, TensorFlow, PyTorch, or YOLO.
• The engineer will create and train deep learning models, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), experimenting with architectures like ResNet, VGG, and EfficientNet.
• Solutions for processing and analyzing large volumes of visual data from images and videos will be developed, including real-time video analytics systems and edge computing applications.
• The role requires preparing and preprocessing datasets for training and evaluation, including data augmentation, image normalization, and labeling.
• Collaboration with software engineers and DevOps teams is essential for deploying computer vision models into production environments using tools like Docker and Kubernetes.
• The engineer will stay updated with advancements in computer vision, deep learning, and AI, exploring technologies such as generative adversarial networks (GANs), 3D vision, augmented reality (AR), and edge AI.
• Close collaboration with product managers, data engineers, and designers will ensure that computer vision capabilities align with business goals and deliver real-world impact.

Requirements:

• Strong knowledge of computer vision techniques, including image classification, object detection, image segmentation, and feature extraction, is required.
• Expertise in deep learning techniques, particularly in convolutional neural networks (CNNs), RNNs, and transfer learning, is essential.
• Proficiency in programming languages such as Python or C++, with experience in writing production-level code, is necessary.
• Experience deploying machine learning models into production environments using cloud platforms (AWS, GCP, Azure) and containerization tools like Docker is required.
• Hands-on experience with data annotation, augmentation, and preprocessing is necessary for working with large datasets.
• A Bachelor’s or Master’s degree in Computer Science, AI, Electrical Engineering, or a related field is required, with equivalent experience in computer vision or machine learning highly valued.
• Certifications or additional coursework in computer vision, deep learning, or AI are considered a plus.
• A minimum of 3 years of experience in computer vision engineering, with a proven track record of building and deploying computer vision models in real-world applications, is required.
• Experience with image and video analysis and developing deep learning models for vision-related tasks is essential.
• Familiarity with cloud-based computer vision services (AWS Rekognition, Google Vision API, Azure Computer Vision) is highly desirable.

Benefits:

• Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums are provided.
• Competitive vacation, sick leave, and 20 paid holidays per year are included in the benefits package.
• Flexible work schedules and telecommuting options promote work-life balance.
• Opportunities for training, certification reimbursement, and career advancement programs support professional development.
• Access to wellness programs, including gym memberships, health screenings, and mental health resources, is available.
• Life insurance and short-term/long-term disability coverage are part of the benefits.
• Confidential counseling and support services for personal and professional challenges are offered through the Employee Assistance Program (EAP).
• Financial assistance for continuing education and professional development is provided through tuition reimbursement.
• Opportunities to participate in community service and volunteer activities are encouraged.
• Employee recognition programs celebrate achievements and milestones.