Computer Vision Intern

FieldAssist; Gurugram District; On-site; INR 167,000 - 279,000; Part time

Job summary

FieldAssist is seeking a Computer Vision Intern to assist in building and refining our image recognition pipeline. The role starts with dataset management—image collection, annotation validation, dataset cleaning, and preprocessing—with hands-on exposure to model training, augmentation, and evaluation for a production-ready pipeline.

You will organize large retail image datasets, validate annotations using Roboflow/CVAT/LabelImg, apply augmentations, train YOLOv5/YOLOv8 models, and help evaluate

Qualifications

• Basic understanding of Computer Vision concepts (Object Detection, Classification).
• Familiarity with Python (OpenCV, Pandas, NumPy).
• Knowledge of image annotation tools (Roboflow, LabelImg, CVAT, etc.).
• Ability to manage and organise large datasets.

Responsibilities

• Organize, clean, and preprocess large-scale retail image datasets.
• Validate and manage annotations (bounding boxes, class labels, segmentation masks if applicable).
• Apply augmentation techniques and prepare datasets for training.
• Support in training YOLOv5/YOLOv8-based models on custom datasets.
• Run model evaluations (Precision, Recall, F1 Score, SKU-level accuracy).
• Collaborate with the product team to improve real-world inference quality.
• Document the dataset pipeline and share insights for improving data quality.

Skills

Computer Vision basics

Python programming

Image annotation tools

Dataset management

Tools

OpenCV

Pandas

NumPy

Roboflow

CVAT

LabelImg

Job description

Computer Vision Intern

We are looking for a Computer Vision Intern to assist in building and refining our image recognition pipeline. The role will start with dataset management—image collection, annotation validation, dataset cleaning, and preprocessing. Once the foundational data work is complete, you’ll get hands‑on exposure to model training, augmentation, and evaluation, contributing directly to our production‑ready pipeline.

Responsibilities

• Organize, clean, and preprocess large-scale retail image datasets.
• Validate and manage annotations (bounding boxes, class labels, segmentation masks if applicable) using tools like Roboflow, CVAT, or LabelImg.
• Apply augmentation techniques and prepare datasets for training.
• Support in training YOLOv5/YOLOv8‑based models on custom datasets.
• Run model evaluations (Precision, Recall, F1 Score, SKU‑level accuracy).
• Collaborate with the product team to improve real‑world inference quality.
• Document the dataset pipeline and share insights for improving data quality.

Who we’re looking for

Must Have

• Basic understanding of Computer Vision concepts (Object Detection, Classification).
• Familiarity with Python (OpenCV, Pandas, NumPy).
• Knowledge of image annotation tools (Roboflow, LabelImg, CVAT, etc.).
• Ability to manage and organise large datasets.

Good to have

• Experience with YOLOv5 or YOLOv8 (Training, Inference, Fine‑tuning).
• Exposure to image augmentation techniques (Albumentations, etc.).
• Understanding of retail/commercial shelf datasets or product detection problems.
• Previous internship or project experience in computer vision is a plus.