16 of 16 Permanent ONNX Jobs in the UK excluding London

Newcastle. Key Responsibilities Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using PySpark. Solid understanding of software engineering principles and version More ❯

Erskine. Key Responsibilities Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using PySpark. Solid understanding of software engineering principles and version More ❯

with Git-based workflows and modern DevOps practices Clear communicator with strong technical documentation skills Nice to Have: Exposure to biotech, life sciences, or cellular imaging domains Experience with ONNX , or deployment of models to production environments A passion for applying AI to biology or scientific data Knowledge of cell line development or biological assay workflows 💡 You’ll Thrive Here More ❯

years in Computer Vision and Deep Learning, with a track record of live deployments in production environments. Proficiency in Python and PyTorch; familiarity with frameworks such as OpenCV, TensorRT, ONNX, or Triton is essential. Knowledge of low-latency performance tuning and multi-threaded programming for real-time processing. Proven experience with object detection and tracking models (e.g., YOLO, Deep SORT More ❯

years in Computer Vision and Deep Learning, with a track record of live deployments in production environments. Proficiency in Python and PyTorch; familiarity with frameworks such as OpenCV, TensorRT, ONNX, or Triton is essential. Knowledge of low-latency performance tuning and multi-threaded programming for real-time processing. Proven experience with object detection and tracking models (e.g., YOLO, Deep SORT More ❯

years in Computer Vision and Deep Learning, with a track record of live deployments in production environments. Proficiency in Python and PyTorch; familiarity with frameworks such as OpenCV, TensorRT, ONNX, or Triton is essential. Knowledge of low-latency performance tuning and multi-threaded programming for real-time processing. Proven experience with object detection and tracking models (e.g., YOLO, Deep SORT More ❯

functionality. Within these tasks, you will have the opportunity to develop skills with the following tools and platforms: Matlab and Simulink Python Deep Learning libraries (e.g. Pytorch, scikit-learn, ONNX) C/C++ Hardware development boards (e.g. NVIDIA Jetson products) Alongside involvement with departmental activities, you will be part of a wider cohort of summer placements and graduates on the More ❯

performance. Requirements 5–7 years of experience in Computer Vision and Deep Learning with deployed production models. Strong proficiency in Python and PyTorch ; hands-on experience with OpenCV, TensorRT, ONNX, or Triton . Proven expertise in object detection/tracking models such as YOLO, Deep SORT, DINOv2 , or similar. Experience with real-time or low-latency processing , multi-threaded programming More ❯

performance. Requirements 5–7 years of experience in Computer Vision and Deep Learning with deployed production models. Strong proficiency in Python and PyTorch ; hands-on experience with OpenCV, TensorRT, ONNX, or Triton . Proven expertise in object detection/tracking models such as YOLO, Deep SORT, DINOv2 , or similar. Experience with real-time or low-latency processing , multi-threaded programming More ❯

performance. Requirements 5–7 years of experience in Computer Vision and Deep Learning with deployed production models. Strong proficiency in Python and PyTorch ; hands-on experience with OpenCV, TensorRT, ONNX, or Triton . Proven expertise in object detection/tracking models such as YOLO, Deep SORT, DINOv2 , or similar. Experience with real-time or low-latency processing , multi-threaded programming More ❯

performance. Requirements 5–7 years of experience in Computer Vision and Deep Learning with deployed production models. Strong proficiency in Python and PyTorch ; hands-on experience with OpenCV, TensorRT, ONNX, or Triton . Proven expertise in object detection/tracking models such as YOLO, Deep SORT, DINOv2 , or similar. Experience with real-time or low-latency processing , multi-threaded programming More ❯

using modern frameworks and libraries. Collaborate with data scientists, engineers, and stakeholders to translate business requirements into technical solutions. Optimize and deploy models using tools like TensorFlow Serving, TorchServe, ONNX, and TensorRT. Build and manage ML pipelines using MLflow, Kubeflow, and Azure ML Pipelines. Work with large-scale data using PySpark and integrate models into production environments. Monitor model performance … Required Skills & Experience Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using PySpark. Solid understanding of software engineering principles and version … in a team. Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using PySpark. Solid understanding of software engineering principles and version More ❯

using modern frameworks and libraries. Collaborate with data scientists, engineers, and stakeholders to translate business requirements into technical solutions. Optimize and deploy models using tools like TensorFlow Serving, TorchServe, ONNX, and TensorRT. Build and manage ML pipelines using MLflow, Kubeflow, and Azure ML Pipelines. Work with large-scale data using PySpark and integrate models into production environments. Monitor model performance … Required Skills & Experience Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using PySpark. Solid understanding of software engineering principles and version … in a team. Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using PySpark. Solid understanding of software engineering principles and version More ❯

during live shopping experiences. Build robust evaluation pipelines that ensure on-device implementations mirror the performance of offline systems. Integrate models with mobile inference backends such as TensorFlow Lite, ONNX Runtime Mobile, MediaPipe or custom native models. Build and manage real-time on-device data stores for low-latency context and lookup. Collaborate with Research Scientists and Research Engineers to … edge devices, ideally Android. Strong proficiency in Python and Java or Kotlin, with experience translating ML code between languages. Practical experience with mobile inference frameworks such as TensorFlow Lite, ONNX Runtime, or similar tools. Familiarity with GPU acceleration on mobile (e.g., GPU delegates, Vulkan) or ARM-based systems is a plus. A mindset that combines engineering rigour with startup adaptability More ❯

during live shopping experiences. Build robust evaluation pipelines that ensure on-device implementations mirror the performance of offline systems. Integrate models with mobile inference backends such as TensorFlow Lite, ONNX Runtime Mobile, MediaPipe or custom native models. Build and manage real-time on-device data stores for low-latency context and lookup. Collaborate with Research Scientists and Research Engineers to … edge devices, ideally Android. Strong proficiency in Python and Java or Kotlin, with experience translating ML code between languages. Practical experience with mobile inference frameworks such as TensorFlow Lite, ONNX Runtime, or similar tools. Familiarity with GPU acceleration on mobile (e.g., GPU delegates, Vulkan) or ARM-based systems is a plus. A mindset that combines engineering rigour with startup adaptability More ❯

during live shopping experiences. Build robust evaluation pipelines that ensure on-device implementations mirror the performance of offline systems. Integrate models with mobile inference backends such as TensorFlow Lite, ONNX Runtime Mobile, MediaPipe or custom native models. Build and manage real-time on-device data stores for low-latency context and lookup. Collaborate with Research Scientists and Research Engineers to … edge devices, ideally Android. Strong proficiency in Python and Java or Kotlin, with experience translating ML code between languages. Practical experience with mobile inference frameworks such as TensorFlow Lite, ONNX Runtime, or similar tools. Familiarity with GPU acceleration on mobile (e.g., GPU delegates, Vulkan) or ARM-based systems is a plus. A mindset that combines engineering rigour with startup adaptability More ❯