Job Title

Key ResponsibilitiesDesign, develop, and deploy deep learning models for image classification, object detection, segmentation, pose estimation, OCR, and related tasks.Work with large-scale datasets (images, videos, annotations), 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 company’s innovation roadmap.Develop tools for model explainability and performance monitoring in production environments.Required QualificationsB.Tech, Master’s 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.Strong skillset in mathematical algorithmics and explainability of deep learning models and frameworks.Preferred SkillsKnowledge of 3D vision, SLAM, multi-view geometry and YOLO.Experience working with video datasets and spatio-temporal models.Background in self-supervised or semi-supervised learning.Familiarity with MLOps pipelines and tools like MLflow, Kubeflow, or SageMakerExperience in a domain-specific application like medical imaging, aerial imagery, or autonomous vehicles.Why Join UsWork on impactful AI products at the cutting edge of computer vision.Collaborate with a world-class team of researchers and engineers.Access to state-of-the-art GPU infrastructure and training platforms.Flexible work environment with competitive compensation and benefits.