9 of 9 ONNX Jobs in England

bottlenecks, and optimizing them Good understanding of docker and containerization (Good to have) experience with Pytorch and Python3, and comfortable with C++ (Good to have) Understanding of Torch script, ONNX runtime, TensorRT (Good to have) Understanding of half-precision inference and int8 quantization What we offer Company equity % in an early-stage startup More ❯

YOLO) for threat and aggression detection. Build reproducible training pipelines (HF/PyTorch/SpeechBrain), incl. PEFT/LoRA, adapters, and transfer learning. Optimize for real-time: quantization, pruning, ONNX/TensorRT, mixed precision, batching, caching. Ship models to edge & cloud with CI/CD, versioning, and rollback; instrument latency and accuracy SLAs. Create data pipelines: collection, labeling, augmentation/ 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 ❯

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 ❯

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 ❯