Intern- Machine Learning (Computer Vision) (QC08632)

Duration: 6 months

Location: Bangalore (In-office)

About the role

We are looking for a Machine Learning Engineering Intern to work on real world computer vision and multimodal AI problems across geospatial, mapping, mining and infrastructure domains.

This role emphasizes building production-ready ML systems, while also contributing to applied research and rapid prototyping. You will work across the full lifecycle from ideation and experimentation to deployment and optimization.

Key Responsibilities

Drive applied research in computer vision, multimodal learning, and 3D perception, translating ideas into practical, product-aligned solutions.

Design and implement novel ML approaches, rapidly iterating from experimentation to real-world prototypes.

Build and deploy production-ready ML pipelines for computer vision and multimodal tasks.

Work on image, video, and 3D (LiDAR/point cloud) data for detection, segmentation, and reconstruction.

Transform research ideas and POCs into scalable, maintainable systems

Collaborate cross-functionally to integrate ML models into product workflows

Required Skills

Currently enrolled in Bachelors/Masters or Phd in Computer Science / AI or related fields (final-year students or fresh graduates preferred).

Strong proficiency in Python, with the ability to write clean, modular, and production-quality code

Hands-on experience with PyTorch (or TensorFlow), and Scikit-learn for training and deploying ML models

Solid understanding of machine learning and computer vision fundamentals such as: Object detection, Semantic / instance segmentation, Feature extraction, 3D reconstruction, Generative models.

Experience with GPU-based training/inference workflows

Very strong attention to detail and ability to work with large datasets efficiently across teams.

Innovative and structured, problem-solving mindset with a curiosity for optimization and automation.

Ability to fully leverage AI to gain speed in development while maintaining code quality.

What You’ll Gain

Hands-on experience building production-grade ML systems, not just experimental models

Exposure to large-scale computer vision and 3D (LiDAR/point cloud) problems in real-world scenarios

Opportunity to work on cutting-edge multimodal AI use cases

Mentorship from experienced engineers working on real-world AI systems at scale

Experience working in a fast-paced environment where your work directly impacts product and customers