Machine Learning Engineer - Computer Vision

Explore Group
London, United Kingdom
8 months ago
Applications closed

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Overview

The Explore Group are working with one of our tier 1 clients in securing an experienced Machine Learning Engineer with strong expertise in Computer Vision to join our team on a 6 month initial contract (with guaranteed extensions). You will play a key role in designing, building, and deploying machine learning models that drive innovation in image and video processing.


Responsibilities

  • Develop, train, and optimise computer vision models for real world applications.
  • Work with large datasets including images and video, ensuring data preprocessing, augmentation, and pipeline optimisation.
  • Deploy ML models into production, ensuring scalability, efficiency, and reliability.
  • Collaborate closely with data scientists, software engineers, and product teams to translate business needs into technical solutions.
  • Stay up to date with the latest advancements in deep learning, computer vision, and related technologies.

Key Skills & Experience

  • Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow).
  • Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn).
  • Proven track record of building and deploying ML models in production environments.
  • Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or similar).
  • Experience working with cloud platforms (AWS, Azure, or GCP).
  • Solid understanding of CNNs, object detection, segmentation, and image classification.
  • Strong problem-solving skills and ability to work in a hybrid, collaborative environment.

Nice to Have

  • Experience with transformer-based vision models (ViT, CLIP, SAM).
  • Familiarity with real-time inference and optimisation (ONNX, TensorRT).
  • Previous work on video analytics, 3D vision, or multi-modal ML projects.

Seniority level

  • Mid-Senior level

Employment type

  • Contract

Job function

  • Consulting

Industries

  • Staffing and Recruiting


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