1 to 25 of 93 CUDA Jobs in England

training and serving foundation models at scale (federated learning a bonus); distributed computing frameworks (e.g., Spark, Dask) and high-performance computing frameworks (MPI, OpenMP, CUDA, Triton); cloud computing (on hyper-scaler platforms, e.g., AWS, Azure, GCP); building machine learning models and pipelines in Python, using common libraries and frameworks ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 the 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 you don’t tick ...

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 ...

environments. Bonus Experience Any of the following would be advantageous: Quantitative finance Machine learning Scientific computing High-performance computing (HPC) Distributed systems GPU programming (CUDA) Optimisation Statistics Numerical methods Time-series modelling Cloud infrastructure Docker or Kubernetes Why This Role? This is an opportunity to work on problems that ...

including public code reviews, documentation, release notes, issue tracking, and community engagement. Vulkan or other low-level graphics and compute APIs, such as OpenCL, CUDA, DirectX, or Metal. Machine learning frameworks, inference runtimes, model formats, or model conversion tooling. CMake, cross-compilation, packaging, dependency management, or developer tooling. Performance ...

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 ...

independently drive research projects from idea generation through experimentation and publication. Nice to Have Experience with classical reconstruction tooling (COLMAP etc). C++ or CUDA, and a feel for performance and on-device constraints. #J-18808-Ljbffr ...

TensorFlow; comfortable with distributed training (DeepSpeed/FSDP/SLURM/K8s). Experience in deep learning, NLP or LLMs; bonus for CUDA or data‐pipeline chops. Strong software‐design instincts: testing, code review, CI/CD. Self‐starter, low‐ego, collaborative. Benefits France 💰 Competitive cash salary and equity ...

industries where reliability and performance are mission‐critical Tech stack Backend: Python Frontend: TypeScript and React Deployment: Kubernetes Infrastructure: GCP Machine learning: PyTorch, CUDA, Ray Why Encord Competitive salary, commission, and meaningful equity in a high-growth startup Strong in-person culture — most of the team works from ...

these — as long as you're open to learning, Backend: Python Frontend: TypeScript and React Deployment: Kubernetes Infrastructure: GCP Machine learning: PyTorch, CUDA, Ray Why Encord Competitive salary, commission, and meaningful equity in a high-growth startup Strong in-person culture — most of the team works from our London ...

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 ...

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 ...

Strong Preference For Experience integrating accelerator hardware (GPUs, FPGAs, ASICs, NPUs, or novel architectures) into customer inference workflows Familiarity with the NVIDIA inference stack - CUDA, TensorRT, Triton Exposure to disaggregated inference architectures, prefill/decode separation, or KV cache management Compensation & Benefits Highly Competitive Salary: We are not saying ...

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 ...

every box, but any exposure to the following would be valuable: High-Performance Computing/HPC C++ Python Rust Java or C# GPU programming CUDA or ROCm Parallel programming Distributed systems Cluster computing Job schedulers or batch-processing frameworks Linux Numerical computing Monte Carlo simulation Quantitative finance Trading technology ...

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 ...

these — as long as you're open to learning, please apply. Backend: Python Frontend: TypeScript and React Deployment: Kubernetes Infrastructure: GCP Machine learning: PyTorch, CUDA, Ray Why Encord Competitive salary, commission, and meaningful equity in a high-growth startup Strong in-person culture — most of the team works from ...