Computer Vision Engineer

About Fogsphere

Fogsphere is a London-based innovator focused on transforming workplace and urban safety through advanced AI, Computer Vision, and Industrial IoT. Built on a principled “Edge-to-Fog-to-Cloud” architecture, our platform turns passive CCTV cameras and sensors into proactive hazard detectors, capable of identifying threats like missing PPE, fire, smoke, restricted access violations, and more-in real time and at scale. This helps organizations across industries-from manufacturing, construction, oil & gas, and healthcare to smart cities-reduce workplace accidents by up to 90%, ensure regulatory compliance (EHS), and gain powerful operational insights. Fogsphere’s intuitive no-code visual workflows, hyper-scalable Kubernetes-based infrastructure, and commitment to ethical AI and privacy (GDPR compliance) make it a user-friendly yet enterprise-grade solution.

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.