Job Description
Responsibilities :
JOB RESPONSIBILITIES:
• Develop, implement, and optimize RCNN-based object detection models (Fast R-CNN, Faster R-CNN, Mask R-CNN, etc.).
• Design and train deep learning models for detection, segmentation, and classification in images.
• Handle and preprocess large-scale image datasets.
• Implement data augmentation and transfer learning techniques to improve model performance.
• Work with GPU-accelerated training frameworks (PyTorch, TensorFlow, CUDA, etc.).
• Develop pipelines for data annotation, preprocessing, and augmentation.
• Conduct error analysis and model interpretability studies to improve model reliability.
• Collaborate with domain experts to fine-tune models.
• Deploy deep learning models into production using cloud services or on-premise infrastructure.
• Stay updated with state-of-the-art research in AI and computer vision.
Requirements :
REQUIREMENTS:
• MSc/PhD in Computer Science, Data Science, AI, or a related field.
• 3+ years of experience in deep learning and computer vision.
• Strong proficiency in Python, PyTorch, TensorFlow, OpenCV.
• Experience with object detection and segmentation models, particularly RCNN variants.
• Solid understanding of convolutional neural networks (CNNs), transformers, and generative models.
• Experience with distributed computing and handling large datasets.
• Knowledge of model deployment and optimization (ONNX, TensorRT, Kubernetes, AWS/GCP/Azure).
• Strong problem-solving skills and ability to work with cross-functional teams.
HIRING TERMS:
• Full-time job
• Five-days working week
• Flexible working hours
• Medical insurance package (family cover)
• Push 30 (Wellness Program)
• Company-provided lunch