Remote Computer Vision Engineer (The Visionary Technologist)
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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.
Responsibilities include designing and implementing advanced 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 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 is necessary to integrate computer vision capabilities into products that align with business goals.
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 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.
A minimum of 3 years of experience in computer vision engineering is required, with a proven track record of building and deploying computer vision models in real-world applications.
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 offered.
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 provided.
Life insurance and short-term/long-term disability coverage are included.
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 encouraged.
Employee recognition programs celebrate achievements and milestones.
Apply now
Please, let Unreal Gigs know you found this job
on RemoteYeah
.
This helps us grow 🌱.