Permanent ONNX Jobs in the City of London

5 of 5 Permanent ONNX Jobs in the City of London

Computer Vision Engineer

City of London, London, United Kingdom
Ultralytics
model robustness on diverse datasets. Leading the full lifecycle of model development, from research and training to validation and performance benchmarking. Mastering model export to various formats such as ONNX, OpenVINO, and TensorRT to support a wide range of hardware. Working on model deployment strategies, including optimizing models for high-performance inference on both cloud and edge devices. Contributing to More ❯
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Machine Learning Engineer - Generative AI

City of London, London, United Kingdom
Qubit Analytics
of publications at top-tier conferences (e.g., NeurIPS, CVPR, ICML, ICLR, SIGGRAPH, ECCV). Experience with GPU programming (CUDA) and model optimization for real-time inference (e.g., quantization, pruning, ONNX, TensorRT, custom CUDA kernels). Background in scalable algorithm design for real-time or interactive applications. Experience integrating machine learning models with complex production pipelines, including 3D graphics or AR More ❯
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Machine Learning Engineer

City of London, London, United Kingdom
Ultralytics
computer vision and a strong understanding of model architectures like transformers and CNNs. Hands-on experience with model optimization (i.e. quantization, pruning) and model deployment frameworks such as TensorRT, ONNX Runtime, and OpenVINO. Proficiency with CUDA programming and optimizing code for GPU acceleration. Strong background in MLOps practices, including CI/CD using GitHub Actions and containerization with Docker. Excellent More ❯
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Staff AI Engineer – Computer Vision & ML

City of London, London, United Kingdom
Brio Digital
Bonus Points For Experience with synthetic data generation and domain adaptation techniques Contributions to open-source ML/CV projects Experience working with mobile ML frameworks (e.g. Core ML, ONNX, TFLite More ❯
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FullStack Automation Engineer

City of London, London, United Kingdom
Humanoid
. Proficiency with containerisation technologies. Experience building simple desktop applications using Wails, Electron, or Tauri. Familiarity with edge/fog computing principles. Familiarity with ML frameworks (e.g., Gorgonia, TensorFlow, ONNX) or prior exposure to integrating pre-trained models via API or runtime interfaces. Practical experience or strong knowledge of IoT and robotics is advantageous. Benefits: High competitive salary. 23 working More ❯
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