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Computer Vision Engineer

About the Role


We are seeking a highly motivated Computer Vision Engineer with a strong background in Deep Learning to join our AI/ML team. You will focus on developing, training, and optimizing models for computer vision applications, working with large-scale image/video datasets, and deploying cutting-edge deep learning solutions into production environments.


Key Responsibilities

  • Design, train, and evaluate deep learning models for computer vision tasks (e.g., classification, detection, segmentation, tracking, retrieval…).
  • VLM fine-tuning.
  • Build and maintain scalable data pipelines for training and evaluation.
  • Optimize model architectures for performance, accuracy, and efficiency (e.g., pruning, quantization, distributed training).
  • Contribute to research and prototyping of novel computer vision algorithms.
  • Deploy trained models into production environments in collaboration with software engineering teams.
  • Document workflows and contribute to team knowledge-sharing.

Qualifications

  • MSc in Computer Vision, Machine Learning, Artificial Intelligence, or related field.
  • 2+ years of hands-on experience in deep learning model development and training.
  • Strong proficiency with Python and ML frameworks (PyTorch, TensorFlow, or Keras).
  • Solid understanding of CNNs, and ViTs
  • Experience with dataset preparation, augmentation, and preprocessing for computer vision.
  • Strong knowledge of optimization techniques, hyperparameter tuning, and evaluation metrics.
  • Good software engineering practices: version control (Git), code testing, reproducibility.
  • Experience working with MLOps frameworks (e.g., MLflow, Weights & Biases, Kubeflow).

Preferred Skills (nice-to-have)

  • Experience on VLM fine-tuning.
  • Knowledge of cloud platforms (AWS, GCP, Azure) for model training and deployment.
  • Background in multimodal AI (vision + language).
  • Contributions to open-source CV/ML projects or publications in top conferences (CVPR, ICCV, NeurIPS, ECCV, TPAMI…).
  • Knowledge on TRT.
  • Experience on edge computing applications.
  • Experience on ANPR and/or Face Recognition, and/or Image Retrieval in general.

What We Offer

  • ZERO micromanagement. At Fogsphere, researchers work independently under the Head of Research, with a focus on open discussion and professional development, where the best ideas are the ones applied.
  • Opportunity to work on cutting-edge computer vision challenges in some of the largest deployments in the field.
  • Possibility to publish papers and collaborate with academia on this task.
  • Collaborative environment with a team of AI researchers and engineers based on multiple countries.
  • Working with academics in the field to help building cutting-edge methods.
  • Competitive salary and benefits package.
  • Career growth and continuous learning opportunities.

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