chainfly

AI/ML Intern (Project-Based) – Transformer & Wire Fault Detection

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New Delhi, Delhi, India Work from home Active
Actively Hiring New Delhi Full Time
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Job Description


V
Vedita Ventures


Java Instructor/Trainers(Work from home/School students/US shift)
Vedita Ventures • via SimplyHired
18 hours ago
Part-time
No Degree Mentioned
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Job description
Job description:

We are currently looking for a subject-matter expert in Java who can teach programming concepts in Java to kids in middle and high school throughout the school year. You must have experience with OOPS and preferably data structures in Java.

Responsibilities:
• You would be responsible for following the lesson plans and teaching programming concepts in Java.
• On a day-to-day bas...
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chainfly


AI/ML Intern (Project-Based) – Transformer & Wire Fault Detection
chainfly • India • via Wellfound
15 hours ago
₹4K–₹6K a year
Internship
Apply directly on Wellfound
Job description
We’re seeking a passionate AI/ML Intern to join a high-impact project focused on building an image-based fault detection model for transformers and wires using Roboflow, Kaggle datasets, and OpenCV. Your goal? Achieve +0%+ accuracy in real-world scenarios.

Type: Remote | Project-Based

Duration: Until model reaches benchmark (Flexible Timeline)

Focus: Object detection, classification, and image pre-processing

What You’ll Do

Collect, clean, and label images from Kaggle and custom sources

Build and train AI models using Roboflow for transformer and wire fault detection

Use OpenCV for image enhancement and preprocessing

Optimize and evaluate the model for +0%+ accuracy

Test the model with real-world images or smartphone datasets

You Are

A student/fresher with knowledge of Computer Vision and Machine Learning

Experienced with Python, OpenCV, Roboflow, and using public datasets (Kaggle)

A critical thinker with a problem-solving mindset

Passionate about fault detection, power infrastructure, or clean tech applications

Bonus

Prior work on transformer, power lines, or electrical component datasets

Familiarity with YOLOv8, CNN, or Vision Transformers
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