5 of 5 CUDA Jobs in Berkshire

modular code delivery in Docker -based environments. Desirable Experience Experience with PyTorch for AI-based perception/control. Familiarity with MoveIt for motion planning in ROS2 . Knowledge of CUDA for C++ real-time optimisation. To Apply: Please email your CV Desired Skills and Experience Python: Advanced proficiency in Python, leveraging scientific and numerical libraries (e.g., NumPy, SciPy) for More ❯

design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research in machine learning are also beneficial. Experience configuring and maintaining cloud infrastructure including network infrastructure, compute More ❯

design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research in machine learning are also beneficial. At a personal level we’re also looking for someone More ❯

optimisation Ability to analyse generated code down to the ISA level Computer architecture knowledge You might also have: Knowledge and experience with graphics/compute APIs such as OpenCL, CUDA, Vulkan, OpenGL or DirectX Experience with compilation specifically for GPUs. Backend compiler development (especially LLVM) An appreciation of multi-threaded and/or parallel computation and associated complexity More ❯

to deploy GPU and ML workloads at scale. Provision and optimise GPU cloud infrastructure (AWS, GCP, Azure) using Terraform/Ansible. Collaborate with GPU engineers and researchers to integrate CUDA, SYCL, Vulkan, and ML kernels into production workflows. Support secure packaging, deployment, and distribution of GPU-accelerated software to partners and clients. Evolve infrastructure to support hybrid AI/… GitLab CI, etc.). Proficiency in containerisation and orchestration (Docker, Kubernetes). Experience with cloud GPU infrastructure (AWS, Azure, GCP) and IaC (Terraform, Ansible). Familiarity with GPU workflows (CUDA, SYCL, Vulkan, OpenCL) or HPC performance optimisation. Strong scripting and programming skills (Python, Bash, C/C++ exposure a plus). Knowledge of monitoring, logging, and performance testing for More ❯