1 to 25 of 108 CUDA Jobs in London

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 Benefits include ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

distributed systems, HPC, or cloud platforms for CPU and GPU workloads.Experience with profiling, benchmarking, or performance analysis.Additional Qualifications (Nice to Have)Familiarity with CUDA or other GPU development frameworks.The minimum base salary for this role is $150,000 if located in New York. This expectation is based on available ...

degree in Computer Science, Computer Engineering, Mathematics, or a highly quantitative field.Preferred Qualifications:Experience with networking protocols (TCP/IP, UDP) or hardware acceleration (CUDA/GPUs).Familiarity with CVS, git and Linux/Unix environments.Basic understanding of quantitative finance and algorithmic trading.Jefferies is a leading global, full-service ...

Computer Science, Computer Engineering, Mathematics, or a highly quantitative field. Preferred Qualifications: Experience with networking protocols (TCP/IP, UDP) or hardware acceleration (CUDA/GPUs).Familiarity with CVS, git and Linux/Unix environments. Basic understanding of quantitative finance and algorithmic trading. Jefferies is a leading global, full ...