Computer Vision Engineer

1–3 years hands-on experience in computer vision or deep learning roles
Exp. with industrial/safety inspection datasets (e.g., PPE detection, visual defect classification)
MLOps tools like MLflow, DVC, or ClearML.
model optimization and deployment frameworks (ONNX, TensorRT, OpenVINO).
Exposure to real-time or edge inference performance constraints.
Contributions to open-source, research publications, or competitive CV challenges (e.g., Kaggle).
Proficiency in Python and deep learning frameworks (PyTorch /Tensorflow).
Good understanding of CNNs, transfer learning, data augmentation,  overfitting mitigation.
Familiarity with basic software engineering practices (git, code reviews, unit testing)

Solid grasp of linear algebra, probability, optimization as applied in ML
Languages/Frameworks: Python, PyTorch, Tensorflow, TorchVision, FastAPI, OpenCV • Model Tools: ONNX TensorRT, Albumentations
DevOps: Docker, Git, Azure/AWS • Infra: Jetson devices, cloud APIs, SQL/NoSQL databases