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.
• The role involves developing innovative algorithms and models that enable computers to process and interpret images and videos.
• 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.
• The position requires developing solutions for processing and analyzing large volumes of visual data, building real-time video analytics systems, and optimizing image processing workflows.
• The engineer will prepare and preprocess datasets for training and evaluation, performing 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 role includes staying updated with advancements in computer vision, deep learning, and AI, and exploring technologies such as generative adversarial networks (GANs), 3D vision, augmented reality (AR), and edge AI.
• The engineer will work closely with product managers, data engineers, and designers to integrate computer vision capabilities into products, ensuring alignment with business goals.

Requirements:

• Strong knowledge of computer vision techniques, including image classification, object detection, image segmentation, and feature extraction, with experience in libraries and frameworks like OpenCV, TensorFlow, PyTorch, or Keras.
• Expertise in deep learning techniques, particularly in convolutional neural networks (CNNs), RNNs, and transfer learning, with experience in building and optimizing models using architectures such as ResNet, VGG, or YOLO.
• Proficiency in Python, C++, or a similar programming language, with experience writing production-level code and efficiently building, testing, and deploying computer vision models.
• Experience deploying machine learning models into production environments using cloud platforms (AWS, GCP, Azure) and containerization tools like Docker, with an understanding of optimizing models for real-time performance.
• Hands-on experience with data annotation, augmentation, and preprocessing, with the ability to work with large datasets and prepare them for training deep learning models.
• A Bachelor’s or Master’s degree in Computer Science, AI, Electrical Engineering, or a related field, with equivalent experience in computer vision or machine learning being highly valued.
• 3+ years of experience in computer vision engineering, with a proven track record of building and deploying computer vision models in real-world applications.
• Proven experience with image and video analysis, and hands-on experience developing deep learning models for vision-related tasks.
• Experience working 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.
• Competitive vacation, sick leave, and 20 paid holidays per year.
• Flexible work schedules and telecommuting options to promote work-life balance.
• Opportunities for training, certification reimbursement, and career advancement programs for professional development.
• Access to wellness programs, including gym memberships, health screenings, and mental health resources.
• Life insurance and short-term/long-term disability coverage for financial security.
• Confidential counseling and support services through an Employee Assistance Program (EAP) for personal and professional challenges.
• Financial assistance for continuing education and professional development through tuition reimbursement.
• Opportunities to participate in community service and volunteer activities for community engagement.
• Employee recognition programs to celebrate achievements and milestones.