1 to 25 of 120 CUDA Jobs in England

CD.Excellent analytical, problem-solving and communication skills.Desirable experienceVision Transformer architectures.Object detection, tracking, segmentation or pose estimation.Multi-object localisation or multi-modal perception systems.GPU optimisation, CUDA, inference acceleration or edge AI.Real-time computer vision systems.Docker, Kubernetes, Kubeflow or MLOps pipelines.Aerial, satellite or ISR imagery.Synthetic data generation, Unreal Engine or NVIDIA ...

communication skills. Desirable experience Vision Transformer architectures. Object detection, tracking, segmentation or pose estimation. Multi-object localisation or multi-modal perception systems. GPU optimisation, CUDA, inference acceleration or edge AI. Real-time computer vision systems. Docker, Kubernetes, Kubeflow or MLOps pipelines. Aerial, satellite or ISR imagery. Synthetic data generation ...

Ways To Stand Out From The Crowd Experience contributing to and working in open-source communities. Experience with the NVIDIA ecosystem, including DGX systems, CUDA, NeMo, RAPIDS, Triton, NIM, and NVIDIA networking technologies such as InfiniBand, NVLink, and RoCE. Experience and familiarity building machine learning systems in a security ...

building things properly the first time, even under early-stage constraints. Nice to Have Experience with GPU cluster management and ML training workloads (NVIDIA, CUDA, distributed training). Familiarity with MLOps tooling: Experiment tracking (MLflow, Weights & Biases). Workflow orchestration (Airflow, Prefect, Argo). Data versioning (DVC). Background ...

into reliable software. Experience developing maintainable code using version control, testing and CI/CD. Strong analytical, problem-solving and communication skills. Desirable experience CUDA and GPU programming. Python and PyTorch. CNNs, Transformers or broader deep learning architectures. Synthetic training imagery and simulation environments. ISR imagery or defence-related ...

Practical MLOps: experiment tracking and model versioning with MLflow, hyperparameter optimisation, and reproducible, configuration-driven training runs. Containerisation and infrastructure as code: Docker and CUDA-based GPU images, plus enough Terraform to ship your own model to an environment through code review rather than a console. Strong software engineering ...

containerisation. AWS or cloud platform experience. FFmpeg or GStreamer. AI, computer vision or multimodal systems. Video curation or data preparation pipelines. GPU technologies including CUDA, PyTorch, TensorRT or Triton. Batch or real-time processing environments. Position : Software Engineer Location : West London Salary : £50-90k Benefits: Pension, Private medical ...

Familiarity with development to design and coding standards . Good teamwork and communication abilities Useful to have Python, C#, LabVIEW software development Experience CUDA integration (AI/ML) Industrial protocols (read-across to Synergia etc.) Experience with Infrared Physics, Computer Science, Software Engineering, ITQSB or Relevant Higher Level Formal ...

engineering: kernel/network tuning, lock-free programming, hardware-aware optimization, or FPGA-adjacent systems.Experience with ML/data tooling such as PyTorch, JAX, CUDA, GPU clusters, Ray, Kafka, Kubernetes, Spark, or comparable technologies.Understanding of market microstructure, backtesting pitfalls, transaction costs, and the operational needs of live quantitative strategies.Experience ...

compute workloads Infrastructure-as-code mindset: Terraform, Ansible, or equivalent; CI/CD pipelines (GitHub Actions, Jenkins, or similar) Experience with hardware-accelerated compute (CUDA/GPU workflows, profiling, performance tuning) — even if not on custom silicon Strong debugging and observability skills: distributed tracing, logging, metrics dashboards Ability ...

managing capacity planning, autoscaling policies, and driving post-incident remediation. Preferred Experience with low-level systems and high-performance computing components (e.g., C++ development, CUDA kernels, NCCL/SHARP, RDMA/NUMA, or GPU interconnect topologies). Active open-source or production contributions to modern inference frameworks (e.g., vLLM ...

camera data processing. Experience with IMU/GNSS‐aided sensor fusion. Experience with C++, C# or Python in engineering software. Familiarity with Linux, Docker, CUDA or GPU acceleration. Understanding of navigation, localisation or mapping products. Familiarity with React or web‐based visualisation tools. Experience using AI coding assistants ...

effectively with trading researchers Reliable and predictable availability required Bonus Points Experience with HPC and distributed large model training Experience with GPU performance optimisation (CUDA or ROCm) Experience with end-to-end model development Strong opinions on best practices in ML research, tooling, and/or infrastructure International Students ...

pipelines and optimizing/productizing ML models. Proficiency in AI/ML frameworks (e.g. PyTorch) and computer vision libraries (e.g., OpenCV, PCL, Open3D, CUDA). Familiarity with various depth sensing modalities (e.g., LiDAR, stereo vision, time‐of‐flight) and sensor fusion. Excellent problem‐solving skills, attention to detail ...

lifecycle of models in a multi‐tenant, high‐availability system. Familiarity with building ML inference services, model serialization (e.g., ONNX), and GPU programming (CUDA). You've built or worked on custom storage or job‐queueing systems before and have the scars to prove it. Maybe ...

with engineering and R&D teams. Programming experience in C, C++, or Fortran, alongside strong Python skills. Experience with GPU programming technologies such as CUDA, OpenACC, or OpenMP Offload. Knowledge of parallel programming frameworks including MPI and OpenMP. Familiarity with build systems, scripting, and batch processing environments. Experience using ...

with engineering and R&D teams. Programming experience in C, C++, or Fortran, alongside strong Python skills. Experience with GPU programming technologies such as CUDA, OpenACC, or OpenMP Offload. Knowledge of parallel programming frameworks including MPI and OpenMP. Familiarity with build systems, scripting, and batch processing environments. Experience using ...

containerisation. AWS or cloud platform experience. FFmpeg or GStreamer. AI, computer vision or multimodal systems. Video curation or data preparation pipelines. GPU technologies including CUDA, PyTorch, TensorRT or Triton. Batch or real-time processing environments. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position : Software Engineer Location : West London Salary : £50-90k Benefits: Pension, Private medical ...

experience working as a Senior Software Engineer with deep expertise in both Python and low-level programming (e.g. C/C++, Rust, assembly or CUDA). A history of direct contributions to vLLM or similar high-performance open-source ML/AI projects (e.g. PyTorch, Hugging Face TGI, TensorRT ...

utilisation across both single-GPU and distributed multi-GPU environments . Improving Python and model inference performance using technologies including NumPy, Numba, Triton and CUDA-based libraries . Conducting load and stress testing to ensure AI services remain performant and stable under high levels of concurrent traffic. Optimising cloud ...

dependable working rhythm. Experience working with HPC environments or training large models in distributed settings, along with some exposure to GPU-level optimisation using CUDA or ROCm. A track record of taking models end-to-end, particularly in the context of LLMs, is valuable. Prior academic publications or meaningful ...

Tune, or similar frameworks Strong engineering practices: reproducible experimentation, clean code, testing, and performance-aware debugging Comfort with modern ML infrastructure (e.g., Docker, CUDA, Kubernetes, experiment tracking tools such as Weights & Biases) PREFERRED Experience with multimodal or multi-task model architectures Training and inference optimization (e.g., mixed precision, kernel ...

modern inference frameworks (e.g., vLLM, Triton, TensorRT‐LLM, Ray Serve, or TorchServe). Deep experience with GPU systems engineering and hardware performance optimisation (e.g., CUDA, NCCL, RDMA, NUMA, or GPU interconnects). Direct exposure to large‐scale AI/ML infrastructure or hyperscale cloud environments. Wondering ...

models.Scale & Performance: Experience training models across distributed systems (multi-GPU/multi-node) and optimising training and inference performance (e.g., XLA, Triton, CUDA, Pallas).Domain Knowledge: A strong interest in, or knowledge of, biochemistry, computational biology, or drug discovery fundamentals.Industry Experience: Proven track record working in reputable tech companies ...

operating large-scale AI, machine learning, or distributed computing platforms in enterprise environments.Deep understanding of LLM architectures and their interaction with GPU infrastructure, including CUDA, cuDNN, NCCL, kernel-level acceleration libraries, and distributed training frameworks such as PyTorch.Strong knowledge of distributed training and inference strategies, including tensor, pipeline, data ...