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Machine learning engineer - computer vision

Stoke-on-Trent
Jr United Kingdom
Machine learning engineer
Posted: 24 August
Offer description

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Machine Learning Engineer - Computer Vision, stoke-on-trent

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Client:

Explore Group


Location:

stoke-on-trent, United Kingdom


Job Category:

Other

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EU work permit required:

Yes

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Job Views:

2


Posted:

22.08.2025


Expiry Date:

06.10.2025

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Job Description:

6 Month Contract - Hybrid Working - Asap Start - Outside of IR-35

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 optimisecomputer vision modelsfor 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.
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