15 of 15 ONNX Jobs in the UK excluding London

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 More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

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 ❯

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 ❯

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 ❯

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 More ❯

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 More ❯

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 More ❯