12 of 12 ONNX Jobs in the UK excluding London

wrangling and analysis using Pandas, NumPy, SQL; familiarity with Spark or similar is a plus. Model optimisation and research-to-prototype deployment fundamentals, including ONNX, TorchScript, FastAPI/gRPC and GPU acceleration, with CUDA basics desirable. Responsible AI and security awareness: explainability, privacy-preserving methods, bias assessment, safety, assurance, adversarial ...

version control and code quality standards. Experience with data processing and analysis tools including Pandas, NumPy, SQL and model deployment technologies such as FastAPI, ONNX or TorchScript. Soft Skills & CollaborationStrong communication skills with the ability to engage technical and non-technical stakeholders. Collaborative approach with experience working effectively within multidisciplinary ...

into production Distributed training frameworks (e.g. Ray, DeepSpeed, PyTorch Lightning) Experiment tracking and model registries (e.g. MLflow or similar) Model optimisation (e.g. ONNX, TensorRT, quantisation) Docker and containerised deployment CI/CD tooling (e.g. GitHub Actions, GitLab CI or similar) Monitoring and observability (e.g. Prometheus, Grafana) Active SC clearance Nice ...

production \n Distributed training frameworks (eg Ray, DeepSpeed, PyTorch Lightning) \n Experiment tracking and model registries (eg MLflow or similar) \n Model optimisation (eg ONNX, TensorRT, quantisation) \n Docker and containerised deployment \n CI/CD tooling (eg GitHub Actions, GitLab CI or similar) \n Monitoring and observability (eg Prometheus ...

image classification, segmentation or visual inspection applications. Real-time processing, GPU acceleration or deployment to edge devices. Model optimisation and inference tools, such as ONNX or TensorRT. Experience working with cameras, video streams or hardware interfaces. Familiarity with Git, CI/CD and AI-assisted coding tools. What You Will ...

have experience across all the areas below. Relevant knowledge, practical experience, or exposure could include: Machine learning inference frameworks such as LiteRT, TensorFlow Lite, ONNX Runtime, or similar technologiesGPU programming or compute technologies such as Vulkan, OpenCL, TOSA, or compute kernelsMachine learning runtimes, compilers, drivers, or backend integrationComputational graphs, operators ...

building machine learning inference engines, runtime systems, or backend integration frameworks. Experience working with a machine learning inference framework such as LiteRT, TensorFlow Lite, ONNX Runtime, or a similar technology is also important. A good understanding of how AI models execute in practice is essential, including graph processing, operator execution ...

demonstrate: Proven product management in development tools and software including CLIs, SDKs and APIs. Knowledge of machine learning frameworks, runtimes, infrastructure such as PyTorch, ONNX, ExecuTorch, Llama.cpp, vLLM and LiteRT.Understanding of model deployment to edge, embedded or heterogeneous computing, with an understanding of trade-offs between accuracy, performance and power ...

compiler stack Developing intermediate representations, lowering pipelines and transformation passes Building hardware-aware compiler optimisations Integrating with technologies such as Google HEIR, PyTorch and ONNX Runtime Translating high-level workloads into efficient code for a novel accelerator Working closely with hardware, simulation, cryptography and algorithms engineers Benchmarking, profiling and debugging ...

aware model optimisation techniques such as quantisation, graph optimisation, operator fusionandprecision reductionExperience across multiple ML frameworks, model formats and inference runtimes, such as PyTorch, ONNX/ONNX Runtime, ExecuTorch, TensorFlow/LiteRT and OpenVINO.Experience analysing, profiling and debugging ML workloads, including model compatibility, performance and the trade-offs between latency ...

NVIDIA is seeking engineers to develop algorithms and optimizations for our LPX inference and compiler stack. You will work at the intersection of large-scale systems, compilers, and deep learning, crafting how neural network workloads ...

models, workloads and application use cases, and translating these into future software and hardware requirements. Working across ecosystems including PyTorch, ExecuTorch, LiteRT and ONNX, plus associated compilers, runtimes and kernel libraries. Evaluating emerging technologies and industry trends to understand their implications for Arm. Required Skills and ExperienceWe are looking … modern AI models and workloads is also required. Candidates should understand the computational characteristics that determine performance on hardware. Familiarity with PyTorch, ExecuTorch, LiteRT, ONNX or ONNX Runtime is important. We also value: Understanding of how AI workloads move through graphs, compilers, runtimes and kernels to hardware. Strong C/ ...