AI engineering intern

Location: Delhi (Hybrid)

Duration: 3 months

Stipend: Competitive, based on skills and experience, with potential for Full-time conversion.

Camarin AI is an early-stage, funded startup building AI-first solutions for fashion e-commerce. Our products focus on improving conversion, personalization, and operational efficiency through applied machine learning and computer vision systems.

Our work spans image segmentation, virtual try-on pipelines, attribute extraction, and vision-driven recommendation systems , all deployed in real-world production environments.

We are looking for an AI Engineering Intern to contribute to production-oriented vision and ML pipelines . This role emphasizes end-to-end ML workflows , experiment tracking, deployment, and iteration in real systems.

You will work closely with senior engineers on developing end-to-end pipelines and model lifecycle management.

• Assist in building and training vision-based models for fashion-tech use cases.
• Work with image datasets: cleaning, preprocessing, augmentation, and validation.
• Contribute to end-to-end ML pipeline development , from training to deployment.
• Integrate models into inference services and internal tooling.
• Containerize training and inference workflows using Docker .
• Maintain clear documentation for experiments, pipelines, and results.

• Strong fundamentals in machine learning, deep learning and computer vision .
• Proficiency in Python and common ML/CV libraries.
• Hands-on experience with PyTorch or TensorFlow .
• Understanding of image preprocessing and data handling for vision tasks.
• Familiarity with ML experiment tracking and orchestration tools such as W&B, MLFlow, AirFlow etc.
• Exposure to end-to-end ML pipeline deployment and basic CI/CD concepts for ML systems.

• Experience with segmentation or other dense prediction problems.
• Exposure to virtual try-on, human parsing, or related vision domains.
• Familiarity with OpenCV, torchvision, albumentations , etc.
• Experience with Docker , model versioning, and artifact management.
• Understanding of inference monitoring and optimization in production.
• Prior exposure to production level systems or experience in a CV-related problem.

• Work on real production ML systems , not academic prototypes.
• Gain hands-on exposure to ML engineering best practices .
• Learn how vision models are deployed and operated at scale.
• Mentorship from engineers shipping real-world AI products.
• Opportunity for full-time conversion based on performance.

Schedule: Day shift

Education:

- Currently pursuing or recently completed a Bachelors or Masters degree in Computer Science, AI, Data Science, or a related field (Preferred).

- Prior experience in a computer-vision heavy domain in terms of research work or production experience is also preferred.

Work Location: Hybrid Delhi