1 to 25 of 92 CUDA Jobs in London

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 ...

necessary Desirable Exposure to computational research involving GPU, including AI/ML methods applied to biomedical problems Experience supporting GPU‐accelerated workloads, NVIDIA tooling, CUDA‐aware environments, and/or AI/ML and bioinformatics workloads on shared compute platforms. Familiarity with bioinformatics or scientific workflow frameworks (e.g., Nextflow ...

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 ...

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 ...

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 ...

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 ...

such as latency, throughput, scalability and cost. Direct development experience with FFmpeg or GStreamer. Experience with GPU-accelerated video or AI technologies such as CUDA, PyTorch, TensorRT, Triton Inference Server or NVIDIA DeepStream. #J-18808-Ljbffr ...

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 ...

Strata, QuantLib, ORE) is an advantage. Hands‐on HPC experience: Parallel/concurrent programming (multithreading, multiprocessing, synchronization, concurrent data structures). GPU compute with CUDA, including GPU architecture (memory hierarchy, warps, occupancy, host–device transfers); ROCm/HIP a plus. Writing and optimizing compute kernels: profiling (e.g. Nsight/ ...

resilience, and results in a high‐performance startup environment. Passion for AI, open source, and helping customers achieve real outcomes. Nice to have Kubernetes, CUDA, TensorRT, ONNX, Jetson, or other edge accelerators. Experience with MLOps, model monitoring, CI/CD, or observability. Familiarity with AWS, Azure, GCP, serverless systems ...

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 ...

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 ...

data structures and algorithms, and a rigorous coding style. Proficient in GPU/NPU architecture, with hands-on development and optimisation experience in CUDA C/C++ or Triton. Strong self-drive and technical curiosity; ability to proactively track the most cutting-edge AI Infra trends in the industry. ...

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 ...

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 ...

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 ...

performance of XTX's training and inference platforms. The remit is wide, and you should expect to be challenged. We are not just writing CUDA code. Amongst other things, you will be working on a sophisticated optimising compiler for a variety of accelerated computing platforms. You should be proficient ...

systems, including vector database management and semantic search optimization. Preferred Qualifications Experience in the insurance or financial services sector. Deep knowledge of GPU architecture , CUDA, and hardware-level performance optimization. Familiarity with Document Intelligence frameworks (OCR, layout analysis, and multimodal extraction). MUST be fluent in Mandarin OR Cantonese ...

complex APIs, third-party libraries, and scalable data pipelines. Desirables: Direct experience with FFmpeg or GStreamer. Familiarity with GPU-accelerated video/AI tech (CUDA, PyTorch, TensorRT, DeepStream). Experience with multimodal AI (VLMs, LLM APIs, Retrieval-Augmented Generation). Cloud and containerization skills (AWS, Docker). ...

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 ...

into existing AI and HPC infrastructure. Its current PT-2 system, a rack-mounted quantum computer, connects directly to GPU clusters via NVIDIA’s CUDA-Q platform, enabling accelerated AI workloads with significantly lower energy consumption than traditional silicon-based systems. Backed by a strong portfolio of patent families ...

Dutch, Swedish, Norwegian, Danish, or Finnish is a plus. Preferred Familiarity with NVIDIA GPU architectures (H100, A100, H200) and the software stack around them: CUDA, NCCL, cuDNN. Working knowledge of high-performance networking concepts: InfiniBand, RDMA, RoCE, TCP/IP. Background working directly with AI labs, research institutions ...

they are looking for a Senior Machine Learning Engineer to join their expanding team in London. Required Experience Strong C++ development skills. Experience with CUDA for GPU acceleration. Python and PyTorch experience. Knowledge of Transformers, computer vision or image analysis. Postgraduate or commercial experience within AI/Machine Learning ...

architectures and model optimisation Excellent software engineering and problem-solving abilities Experience working with complex datasets and real-world machine learning challenges Desirable Skills CUDA TensorRT Triton Quantised model training Edge AI deployment Computer Vision Robotics or autonomous systems Advanced C++ development Synthetic data generation What We're Looking ...