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Machine Learning Intern at Atlys in Delhi – Computer Vision and Model Fine-Tuning Internship

Machine Learning Intern at Atlys in Delhi – Computer Vision and Model Fine-Tuning Internship

Sourced from careers.atlys.com

ML Intern

Delhi
Full-Time
Posted April 9, 2026
Salary
40K-65K/Month
Batches
2026,2027
Apply Route
100% Direct

About The Role

Atlys is a fast-growing technology startup focused on simplifying global travel documentation and visa-related processes through intelligent digital systems. The company uses automation, machine learning, and data-driven workflows to reduce friction in document handling and improve customer experience across travel operations. Machine learning plays an important role in extracting structured information, validating documents, and improving image quality for automated processing pipelines. This internship is ideal for candidates who want practical experience applying computer vision and modern ML techniques to real product problems in a fast-moving startup environment 🌍🤖.

Responsibilities

Train and fine-tune machine learning models for image quality detection and enhancement tasks.
Run structured experiments to compare model architectures and evaluate performance.
Prepare and validate labeled datasets for extracting structured information such as names, dates, and numerical fields.
Write Python scripts to automate repetitive data processing workflows.
Document model training procedures, experiment outcomes, and technical observations clearly.
Support iterative improvements in model accuracy and robustness for production use cases.

Requirements

  • Strong Python programming skills with ability to write clean automation scripts.
  • Familiarity with PyTorch or TensorFlow through projects, coursework, or competitions.
  • Understanding of computer vision fundamentals including augmentation and common architectures.
  • Knowledge of image processing concepts and practical model experimentation.
  • Strong attention to detail in data preparation and validation.
  • Ability to document work clearly and systematically.

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