Computer Vision Internship at IG Drones ₹30,000/month

Are you passionate about computer vision, deep learning, and cutting-edge AI technologies? The Computer Vision Internship at IG Drones Bangalore offers an exceptional 6-month opportunity with ₹15,000-30,000 monthly stipend to work on real-world drone-based computer vision applications for government and enterprise clients.

IG Drones is a Government of India-supported company delivering cutting-edge technology solutions for infrastructure, power, railways, smart cities, and more. With clients including Indian Railways, Power Grid Corporation, Adani Group, Aditya Birla Group, and multiple state governments, this internship provides hands-on experience with production-grade computer vision systems deployed on edge devices for critical applications.

🚀 About the Computer Vision Internship at IG Drones

This 6-month full-time, in-office internship focuses on designing and developing computer vision algorithms for drone-based image and video analysis. You’ll work with deep learning models, object detection, tracking, segmentation, and pose estimation while optimizing solutions for edge deployment on devices like Jetson and ARM processors. The role provides comprehensive exposure to real-time pipelines, model optimization, and deployment in challenging real-world conditions.

📊 Internship Details

About IG Drones

Company Overview

IG Drones is a leading drone technology company with strong government backing:

• Government Support: Backed by Government of India and state governments of Gujarat and Odisha
• Corporate Office: Ahmedabad, Gujarat
• Zonal Offices: Delhi, Mumbai, Bhubaneswar, Patna, Bangalore
• Mission: Delivering global cutting-edge technology solutions for localized needs

Primary Internship Responsibilities

Computer Vision Algorithm Development

• Design and develop computer vision algorithms for analyzing images and video streams from drones
• Build robust solutions for aerial imagery analysis and real-time video processing
• Implement algorithms for feature extraction, pattern recognition, and anomaly detection
• Work on multi-camera fusion and sensor integration
• Develop algorithms optimized for drone-specific challenges (motion, altitude, lighting)

Deep Learning Model Development

• Build and optimize deep learning models including CNNs, Transformers, and multi-modal models
• Design architecture for specific computer vision tasks based on requirements
• Experiment with state-of-the-art architectures and adapt them for drone applications
• Implement transfer learning and domain adaptation techniques
• Work with attention mechanisms and vision transformers

Computer Vision Tasks Implementation

• Implement object detection for identifying infrastructure defects, assets, and objects of interest
• Develop tracking algorithms for following objects across video frames
• Build segmentation models for precise boundary detection and area measurement
• Create pose estimation systems for structural analysis and monitoring
• Implement classification models for categorizing detected objects and conditions

Model Training and Optimization

• Train models using real-world datasets collected from drone operations
• Evaluate model performance using appropriate metrics and validation techniques
• Fine-tune pre-trained models for specific use cases and domains
• Implement data augmentation strategies for improving model robustness
• Optimize hyperparameters through systematic experimentation
• Handle class imbalance and dataset biases effectively

Edge Device Optimization

• Optimize deep learning models for edge devices including Jetson, ARM processors, and GPUs
• Reduce model size and computational requirements without sacrificing accuracy
• Implement quantization, pruning, and knowledge distillation techniques
• Ensure real-time inference on resource-constrained hardware
• Balance accuracy, speed, and memory footprint for deployment

Real-Time Pipeline Development

• Work with real-time video processing pipelines using RTSP, GStreamer, OpenCV, and CUDA
• Implement efficient data preprocessing and post-processing pipelines
• Optimize frame processing for low-latency applications
• Handle video streaming protocols and synchronization
• Integrate GPU acceleration for real-time performance

Model Deployment

• Deploy optimized models using TensorRT, ONNX, and TorchScript formats
• Implement inference engines for production deployment
• Create APIs and interfaces for model serving
• Ensure deployment stability and error handling
• Monitor deployed model performance and resource usage

Model Robustness Enhancement

• Improve model robustness under varying lighting conditions (day/night, shadows)
• Handle different weather conditions (rain, fog, dust)
• Address motion blur and vibration challenges in drone footage
• Implement strategies for handling occlusions and partial visibility
• Ensure consistent performance across diverse environmental conditions

Cross-Functional Collaboration

• Collaborate with hardware teams on sensor integration and drone platforms
• Work with firmware engineers on embedded system integration
• Partner with product teams to understand requirements and user needs
• Coordinate with deployment teams for field testing and validation
• Share insights and learnings across teams

Documentation and Reporting

• Document experiments, methodologies, and results systematically
• Maintain comprehensive records of model architectures and configurations
• Track system performance metrics and improvements
• Create technical documentation for deployment and maintenance
• Present findings and progress to stakeholders regularly

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📋 Required Qualifications and Skills

Required Technical Skills

Educational Background

• Pursuing or completed B.E/B.Tech/M.Tech in Computer Science, Electronics, or related field
• Strong academic background in mathematics and programming
• Relevant coursework in computer vision, deep learning, or AI
• Academic projects involving CV or ML

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💰 Stipend and Benefits

Monthly Compensation

Total Stipend (6 months): ₹90,000 – 1,80,000

Eligibility Criteria

Availability Requirements

• Available for full-time in-office internship (mandatory)
• Can start between 3rd February 2026 and 10th March 2026
• Available for complete 6-month duration
• Based in or willing to relocate to Bangalore

Skills and Interests

• Have relevant skills in computer vision, deep learning, and Python
• Demonstrated interest through projects, coursework, or previous internships
• Passion for AI and computer vision technologies

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How to Prepare for the Application

Technical Preparation

• Master OpenCV and build image processing projects
• Gain proficiency in PyTorch or TensorFlow with CV applications
• Implement object detection models (YOLO, Faster R-CNN) from scratch
• Practice model optimization and quantization techniques

Project Portfolio

• Build 2-3 computer vision projects demonstrating different techniques
• Include object detection, segmentation, or tracking projects
• Deploy at least one model on edge device (Raspberry Pi, Jetson)
• Create GitHub repository with well-documented code

Edge Computing Focus

• Learn TensorRT or ONNX for model optimization
• Understand quantization and model compression
• Practice deploying models on resource-constrained devices
• Explore GStreamer for video pipeline development

Interview Readiness

• Review computer vision fundamentals and deep learning concepts
• Prepare to discuss CV projects in technical depth
• Understand trade-offs in model design for edge deployment
• Practice explaining complex algorithms clearly

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Application Tips

• Highlight computer vision projects with clear technical details and results
• Showcase deep learning experience with PyTorch or TensorFlow
• Emphasize any edge deployment or model optimization work
• Include metrics and performance benchmarks in project descriptions
• Mention experience with aerial imagery or drone data if available
• Express genuine interest in drone technology and real-world applications
• Prepare to discuss trade-offs between accuracy and inference speed
• Research IG Drones’ application areas and client projects
• Show understanding of challenges in deploying CV on edge devices
• Include GitHub profile with well-documented CV projects
• Mention any publications, competitions, or certifications in CV/DL
• Apply early as deadline is 5 March 2026

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