Computer Vision Trainer

Technology Pvt. Ltd.; Patna; Remote; INR 964,000 - 1,791,000; Part time

Job summary

Technology Pvt. Ltd. invites applications for a freelance Computer Vision Trainer. The role focuses on designing, developing, and delivering engaging CV courses for individuals and groups, including beginners to advanced learners.

Responsibilities include live online teaching, content creation, and student assessment, with ongoing updates to keep pace with new CV trends and tools. Fresh graduates and experienced professionals are welcome to apply.

Qualifications

• Minimum 2–5 years in computer vision or related field.
• Experience in teaching/training, especially online or freelance.
• Proficient with OpenCV, TensorFlow, Keras or PyTorch.
• Certifications in CV or DL are preferred but not mandatory.
• Excellent communication and ability to explain complex CV topics.

Responsibilities

• Design and deliver computer vision training courses for different levels.
• Develop instructional materials including presentations, datasets, and exercises.
• Conduct live online training sessions and monitor learner progress.
• Assess students through quizzes and projects and provide feedback.
• Mentor students and update curriculum with latest CV trends and tools.

Skills

Teaching

Communication

Curriculum Design

Student Assessment

Education

Bachelor's degree in Computer Vision/Data Science/CS/Engineering

Tools

OpenCV

TensorFlow

Keras

PyTorch

YOLO/Faster R-CNN

Job description

Job Description: We are seeking a skilled Computer Vision Trainer to deliver engaging and effective training sessions for individuals and groups. This role is ideal for both experienced professionals and fresh graduates who are passionate about teaching computer vision concepts, techniques, and applications. As a freelance Computer Vision Trainer, you will design, develop, and conduct courses covering various aspects of computer vision.

Key Responsibilities:

• Course Development: Design and develop comprehensive training programs in computer vision, tailored to various skill levels, including beginner, intermediate, and advanced learners. Topics include image processing, object detection, image classification, and deep learning for computer vision.
• Content Creation: Create and update instructional materials such as presentations, coding exercises, datasets, and real-world case studies that reflect current computer vision practices and technologies.
• Training Delivery: Conduct live, interactive training sessions via online platforms, focusing on essential computer vision skills such as image manipulation, feature extraction, and model training and evaluation.
• Student Assessment: Evaluate student performance through quizzes, assignments, and practical projects. Provide constructive feedback to enhance their understanding and application of computer vision concepts.
• Support and Mentorship: Offer personalized support to students, addressing their questions and assisting with troubleshooting issues related to computer vision techniques, tools, and methodologies.
• Continuous Improvement: Stay updated with the latest trends and advancements in computer vision, including new techniques, tools, and research, and integrate these advancements into the training curriculum.

Qualifications:

For Experienced Professionals:

• Experience: Minimum of 2-5 years of professional experience in computer vision, with hands-on experience in applying computer vision techniques to real-world problems.
• Teaching Experience: Previous experience in teaching or training, especially in a freelance or online setting, is highly desirable.
• Technical Skills: Proficiency in computer vision libraries and frameworks such as OpenCV, TensorFlow, Keras, or PyTorch. Experience with deep learning models for computer vision (e.g., CNNs, object detection models like YOLO, Faster R-CNN) is essential.
• Certifications: Relevant certifications in computer vision or related fields (e.g., Deep Learning Specialization, Computer Vision with TensorFlow) are preferred but not mandatory.
• Communication Skills: Strong communication skills with the ability to clearly and effectively explain complex computer vision concepts and techniques.

For Freshers:

• Education: A degree or certification in Computer Vision, Data Science, Computer Science, Engineering, or a related field.
• Technical Skills: Basic knowledge of computer vision techniques and tools, gained through academic coursework, internships, or personal projects. Familiarity with libraries such as OpenCV or TensorFlow is a plus.
• Passion for Teaching: A strong interest in teaching and mentoring students in computer vision, with a commitment to developing effective training methods.
• Communication Skills: Excellent verbal and written communication skills, capable of making complex computer vision topics understandable to diverse audiences.