13 of 13 Remote CUDA Jobs in Berkshire

AI/ML in the sports domain to create insights or data. Advanced systems knowledge, such as: Developing GPU kernels or ML compilers (e.g., CUDA, OpenCL, TensorRT Plugins, MLIR, TVM ). System optimization for latency and utilization , using tools like Nvidia NSight . Working with embedded SoCs (e.g., Nvidia More ❯

solutions. Proficiency in C++. Desirable experience: PhD in computer vision or robotics. Experience with machine learning techniques for geometric & semantic estimation. GPU programming skills (CUDA, OpenCL, Vulkan, Metal). Experience with embedded software development. If this role is of any interest please apply directly on LinkedIn or send a More ❯

Sports tech experience: Background applying AI/ML in the sports domain for data generation or insights. Systems optimisation: Knowledge of GPU kernel development (CUDA, OpenCL, etc.), real-time system optimisation (e.g., Nvidia NSight), or experience working with embedded SoCs (Nvidia, Qualcomm, etc.). If you're interested in More ❯

Hands-on with monitoring tools like Prometheus and Grafana Nice to have: Experience building Developer Experience (DevX) tools and workflows Familiarity with GPU setups (CUDA, TensorFlow, etc.) Strong networking and network security knowledge Linux/Unix skills and shell scripting A degree in Computer Science or a related field More ❯

scale. Essential Requirements: Proven experience as an Engineering Manager delivering complex engineering projects. Expertise in developing GPU kernels and/or ML compilers (e.g., CUDA, OpenCL, TensorRT, MLIR, TVM). Experience optimizing systems to meet strict utilization and latency requirements. Excellent interpersonal and communication skills. Desirable: Experience with C++ More ❯

Graphics Hardware Processors (5 - 10+ years' experience) Strong understanding of modern 3D graphics and/or compute APIs, such as Vulkan, D3D12 and OpenCL, CUDA etc. Definition of high-level GPU architecture/micro-architecture Confidence knowledge in the ASIC digital design flow Experience in R&D of the More ❯

Graphics Hardware Processors (5 - 10+ years' experience) Strong understanding of modern 3D graphics and/or compute APIs, such as Vulkan, D3D12 and OpenCL, CUDA etc. Definition of high-level GPU architecture/micro-architecture Confidence knowledge in the ASIC digital design flow Experience in R&D of the More ❯

deep understanding of transformers, LLMs, and multimodal models Hands-on experience with distributed training frameworks like DeepSpeed or FSDP Solid background in GPU programming (CUDA, ROCm) and inference optimisation Practical experience with parameter-efficient fine-tuning techniques in real-world applications Familiarity with container orchestration tools (Kubernetes, Kubeflow) and More ❯

Flux, and similar architectures 🚀 Experience fine-tuning and optimising visual models 🚀 Hands-on experience with PyTorch, JAX, or TensorFlow 🚀 Proficiency in GPU inference optimisation (CUDA, BitsAndBytes, PEFT) 🚀 Experience deploying ML models using Kubernetes and/or Docker 🚀 Strong experience with Python and software engineering best practices 🚀 Experience integrating visual More ❯

with low-level system and memory management techniques to minimize latency and improve real-time inference performance. Utilizing and implementing GPU programming APIs (e.g., CUDA, OpenCL) to ensure high efficiency and compatibility across GPUs. Profiling and debugging system performance using tools like NVIDIA Nsight, Intel VTune, and vendor-specific … years of experience in C++ programming, with a strong grasp of modern C++ standards. Proven experience in GPU programming and optimization, with proficiency in CUDA, OpenCL, or other GPU programming frameworks. Strong knowledge of parallel computing concepts, including data locality, memory access patterns, and synchronization. Proficiency with performance profiling More ❯

or embedded environments Proficient in modern C++ development Preferred Familiarity with machine learning for semantic/geometric inference. Experience in GPU computing, e.g. Vulkan, CUDA, OpenCL or Metal Exposure to embedded systems development. Feel free to also refer someone you may know who could be good for the role. … If they are successfully placed, we offer a great referral scheme! Key words – SLAM/State Estimation/Computer Vision/Robotics/CUDA/Vulkan/OpenCL/Metal/Sensor Fusion/Embedded Systems/Semantic Inference/Geometric Inference/C++/Spatial AI By applying More ❯

to hear from you.) 💡 The Stack & Environment: A diverse, modern environment spanning: Linux, Windows, MacOS, Microsoft 365, Azure AD, Intune, Teams, NICE DCV, Nvidia CUDA, Slurm, Jira Service Desk, Terraform, Azure Resource Manager 💡 What We’re Looking For: 2+ years of experience administering HPC infrastructure Hands-on experience with … Infiniband, Slurm, and GPU compute platforms (e.g. CUDA) Proficiency in systems administration and troubleshooting Strong documentation habits and a customer-focused mindset Experience with VDI solutions and monitoring tools 💡 Bonus Points: Familiarity with Jira Service Desk and Terraform scripting Exposure to SSL management, infrastructure-as-code, or cloud database More ❯

Stack & Environment: Work across a modern tech landscape including: Linux, Windows, MacOS, Microsoft 365, Azure AD, Intune, Teams (incl. voice integration), NICE DCV, Slurm, CUDA, Jira Service Desk, Terraform, SiteGround, Confluence, and more 💡 What We’re Looking For: 2+ years of experience in IT support or service desk operations … across Windows, Linux, and MacOS Experience with Microsoft cloud environments and endpoint management Clear communicator with good documentation practices 💡 Bonus Points: Exposure to Slurm, CUDA, Infiniband, or NICE/Amazon DCV Experience with infrastructure automation or scripting (e.g. Terraform) Understanding of SSL management and monitoring tools like Site24x7 Familiarity More ❯