Remote Computer Vision Engineer (The Visionary Technologist)

Description:

• The Computer Vision Engineer will design, implement, and optimize computer vision systems that power transformative applications across various industries.
• This role involves developing innovative algorithms and models that allow computers to process and interpret images and videos.
• The engineer will work closely with data scientists, AI researchers, and product teams to create vision-based AI systems that interpret visual data with accuracy and efficiency.
• 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, such as CNNs and RNNs, and experiment 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 to deploy computer vision models into production environments using tools like Docker and Kubernetes.
• The engineer will stay updated with the latest advancements in computer vision, deep learning, and AI, exploring technologies such as GANs, 3D vision, AR, and edge AI.
• Cross-functional collaboration with product managers, data engineers, and designers is necessary to integrate computer vision capabilities into products.

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 CNNs, RNNs, and transfer learning, is essential.
• Proficiency in Python, C++, or a similar programming language, with experience 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 essential.
• 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 a plus.
• A minimum of 3 years of experience in computer vision engineering is required, with a track record of building and deploying computer vision models in real-world applications.
• Proven experience with image and video analysis and developing deep learning models for vision-related tasks is necessary.
• 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 are provided.
• Competitive vacation, sick leave, and 20 paid holidays per year are included.
• Flexible work schedules and telecommuting options promote work-life balance.
• Opportunities for training, certification reimbursement, and career advancement programs are available for professional development.
• Access to wellness programs, including gym memberships, health screenings, and mental health resources, is offered.
• Life insurance and short-term/long-term disability coverage are provided.
• Confidential counseling and support services for personal and professional challenges are available through the Employee Assistance Program (EAP).
• Financial assistance for continuing education and professional development is offered through tuition reimbursement.
• Opportunities to participate in community service and volunteer activities are available for community engagement.
• Employee recognition programs celebrate achievements and milestones.