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Computer Vision Intern

2 weeks ago

Gurgaon, Haryana, India Weekday AI Full time ₹ 5,00,000 - ₹ 10,00,000 per year

This role is for one of the Weekday's clients

Min Experience: 0 years

Location: Gurgaon

JobType: full-time

We are seeking a Computer Vision Intern to contribute to advancing our AI-powered visualization tools. The ideal candidate will have hands-on experience with computer vision, deep learning, and machine learning techniques. You will work on improving visual accuracy and realism by leveraging models such as Stable Diffusion and other generative AI technologies. This is an opportunity to apply cutting-edge research to real-world applications and shape the future of AI-driven visualization.

Requirements

Key Responsibilities
  • Evaluate and select appropriate models for specific tasks through R&D.
  • Fine-tune deep neural networks on custom datasets.
  • Benchmark and analyze model performance.
  • Integrate trained models into production environments.
  • Optimize inference using methods such as quantization.
Qualifications
  • Currently pursuing or recently graduated with a Bachelor's/Master's in Computer Science, Electronics & Communication, or related fields.
  • Proficiency in Python (C++ knowledge is a plus).
  • Understanding of core deep learning concepts: regression, classification, gradient descent, backpropagation, regularization, CNNs, transformers, GANs, diffusion models, etc.
  • Exposure to computer vision techniques: image generation pipelines, object detection (YOLO, Faster R-CNN), epipolar geometry, photogrammetry, etc.
  • Familiarity with computer graphics concepts: rasterization, global illumination, spatial data structures, etc.
Technical Skills

CNNs, Diffusion Models, 3D Vision, Object Detection, Image Processing, PyTorch, Computer Vision, Deep Learning, Machine Learning, Generative AI

Soft Skills
  • Strong analytical and problem-solving abilities.
  • Clear communication skills to explain complex ideas and architectures.
  • Proactive, collaborative, and eager to contribute in a team environment.