1 to 25 of 50 Permanent OpenCV Jobs in the UK excluding London

analysis. Proficiency in Python 3.9+, with a solid understanding of object-oriented programming and data structures. Experience with libraries such as PyTorch, OpenCV, PIL/Pillow, and Hugging Face for working with AI/ML models. Familiarity with AWS services, including Lambda, S3, CloudWatch, and Boto3 for automation ...

Python, with familiarity in CUDA for GPU acceleration. Full UK Driving License. Advantageous/Preferred Requirements: Proficiency in perception and computer vision techniques, including OpenCV, image processing, and 3D point cloud processing. Hands-on expertise with deep learning frameworks like TensorFlow or PyTorch, and knowledge of CNNs, RNNs ...

experience in the following areas: 1. Bachelor's in Computer Science, Software Engineering or a related field. 2. Experience with image processing libraries (e.g. OpenCV, PIL, scikit-image) or numerical analysis (NumPy, SciPy). 3. Solid understanding of React/JavaScript/Typescript for web or mobile app development. ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...

/CV concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able ...