Data Scientist - Computer Vision (Bangalore Division)

As a Computer Vision Engineer, your role involves designing, developing, and deploying deep learning models for various computer vision tasks such as image classification, object detection, segmentation, pose estimation, OCR, and more. You will work with large-scale datasets, including data cleaning, augmentation, and preprocessing pipelines. Your responsibilities will also include evaluating and fine-tuning models using metrics like IoU, mAP, F1 score, and accuracy. Additionally, you will conduct research and experimentation with state-of-the-art architectures and collaborate with cross-functional teams to integrate models into production pipelines. Key Responsibilities: - Design, develop, and deploy deep learning models for image classification, object detection, segmentation, pose estimation, OCR, and related tasks. - Work with large-scale datasets, including data cleaning, augmentation, and preprocessing pipelines. - Evaluate and fine-tune models using metrics like IoU, mAP, F1 score, and accuracy. - Conduct research and experimentation with state-of-the-art architectures such as CNNs, Transformers (ViT, DETR), GANs, and self-supervised learning. - Collaborate with cross-functional teams to integrate models into production pipelines (cloud/on-prem). - Stay current with the latest advancements in computer vision and contribute to the companys innovation roadmap. - Develop tools for model explainability and performance monitoring in production environments. Qualifications Required: - B.Tech, Masters or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, or a related field. - 3+ years of experience in developing and deploying deep learning models for computer vision tasks. - Strong proficiency in Python and deep learning frameworks like PyTorch and TensorFlow. - Hands-on experience with libraries such as OpenCV, Albumentations, MMDetection, Detectron2, or YOLOv5/8. - Experience training and optimizing models on GPU clusters using distributed training (e.g., PyTorch Lightning, DDP). - Familiarity with model deployment (ONNX, TensorRT, TorchScript) and serving (FastAPI, Flask, Triton Inference Server). - Experience with annotation tools (e.g., CVAT, Labelbox) and data versioning tools (e.g., DVC, Weights & Biases). - Strong understanding of computer vision metrics and evaluation protocols. - Solid skillset in mathematical algorithmics and explainability of deep learning models and frameworks. In addition to the above responsibilities and qualifications, the company offers competitive compensation and benefits, the opportunity to work on cutting-edge quantum computing and semiconductor R&D projects, and a collaborative and research-driven work environment. Join us to work on impactful AI products at the cutting edge of computer vision, collaborate with a world-class team of researchers and engineers, access state-of-the-art GPU infrastructure and training platforms, and enjoy a flexible work environment with competitive compensation and benefits. As a Computer Vision Engineer, your role involves designing, developing, and deploying deep learning models for various computer vision tasks such as image classification, object detection, segmentation, pose estimation, OCR, and more. You will work with large-scale datasets, including data cleaning, augmentation, and preprocessing pipelines. Your responsibilities will also include evaluating and fine-tuning models using metrics like IoU, mAP, F1 score, and accuracy. Additionally, you will conduct research and experimentation with state-of-the-art architectures and collaborate with cross-functional teams to integrate models into production pipelines. Key Responsibilities: - Design, develop, and deploy deep learning models for image classification, object detection, segmentation, pose estimation, OCR, and related tasks. - Work with large-scale datasets, including data cleaning, augmentation, and preprocessing pipelines. - Evaluate and fine-tune models using metrics like IoU, mAP, F1 score, and accuracy. - Conduct research and experimentation with state-of-the-art architectures such as CNNs, Transformers (ViT, DETR), GANs, and self-supervised learning. - Collaborate with cross-functional teams to integrate models into production pipelines (cloud/on-prem). - Stay current with the latest advancements in computer vision and contribute to the companys innovation roadmap. - Develop tools for model explainability and performance monitoring in production environments. Qualifications Required: - B.Tech, Masters or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, or a related field. - 3+ years of experience in developing and deploying deep learning models for computer vision tasks. - Strong proficiency in Python and deep learning frameworks like PyTorch and TensorFlow. - Hands-on experience with libraries such as OpenCV, Albumentations, MMDetection, Detectron2, or YOLOv5/8. - Experience training and optimizing models on GPU c