AI Engineer - Computer Vision

Iqud Tek; Gandhinagar; On-site; INR 201,000 - 290,000; Full time

Job summary

Iqud Tek in Gandhinagar, Gujarat offers an AI Engineer Internship focusing on computer vision. You will design, train, optimize, and deploy vision-based AI systems across varied domains from healthcare to manufacturing.

The role provides hands-on experience with large datasets, production-grade modeling, and exposure to modern architectures, tools, and cloud/container workflows in an office setting.

Qualifications

• Pursuing a bachelor’s degree in a relevant field (CS/EE/AI).
• Strong programming with Python and ML fundamentals essential.
• Hands-on experience with CV workflows and data annotation preferred.

Responsibilities

• Develop, train, and optimize computer vision models for detection, segmentation, OCR, and analytics.
• Build data pipelines for image/video ingestion, cleaning, augmentation, and annotation workflows.
• Evaluate models using metrics such as mAP, IoU, F1, precision, recall, latency, and accuracy.
• Deploy models in production environments using frameworks like TensorFlow, PyTorch, ONNX Runtime, or OpenVINO.
• Create scalable inference APIs and integrate models with backend systems.

Skills

Python

Deep learning

PyTorch

TensorFlow

OpenCV

NumPy

Model training

CV pipelines

Education

Pursuing B.Tech/B.E. in CS/EC/AI

Tools

OpenCV

NumPy

ONNX Runtime

Job description

AI Engineer - Computer Vision

Location: GIFT City, Gandhinagar, Gujarat - India. (Work from Office)

Experience: Internship (Full-Time)

About the Role

We are hiring an enthusiastic AI Engineer Intern with a strong interest in Computer Vision to join our team at GIFT City. You will get hands‑on experience designing, training, optimizing, and deploying vision‑based AI systems used across healthcare, fintech, manufacturing, retail automation, and enterprise applications.

This internship is ideal for learners who want real exposure to AI development, large‑scale datasets, and production‑grade model building for global use cases.

Key Responsibilities:

• Develop, train, and optimize Computer Vision models for object detection, segmentation, OCR, anomaly detection, rPPG‑based vitals extraction, and custom video analytics.
• Build robust data pipelines for image/video ingestion, cleaning, augmentation, and annotation workflows.
• Perform model evaluation using standard metrics such as mAP, IoU, F1, precision, recall, latency, and accuracy.
• Deploy models to production using TensorFlow, PyTorch, ONNX Runtime, or OpenVINO.
• Develop scalable inference APIs and integrate models with backend systems.
• Implement model optimization techniques including quantization, pruning, distillation, and GPU acceleration.
• Research and experiment with modern architectures like Transformers, YOLO variants, RNN/CNN hybrids, and lightweight mobile models.
• Collaborate with DevOps teams to containerize inference workloads using Docker and deploy on cloud platforms.
• Document experiments, results, and best practices clearly for internal teams and clients.

Required Skills

• Strong proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).
• Solid understanding of machine learning algorithms and computer vision fundamentals.
• Experience with OpenCV, NumPy, and image/video preprocessing.
• Hands‑on experience with datasets, annotations, and CV pipeline design.
• Ability to train, validate, and tune deep learning models.
• Familiarity with deploying ML workloads on cloud or containerized environments.
• Good analytical and debugging skills.

Nice-to-Have Skills

• Experience with YOLOv7/8, Detectron2, MediaPipe, OpenVINO, or ONNX Runtime.
• Exposure to rPPG signal extraction, vitals estimation, and video-based biometrics.
• Understanding of MLOps tools and practices.
• Knowledge of AWS, GCP, or Azure ML services.
• Experience with GPU optimization and real-time model performance tuning.