26 to 50 of 143 CUDA Jobs

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 ...

training frameworks, GPU/accelerator optimisation, data pipelines, experiment tracking, and making research reproducible and reliable. You have experience down to the level of CUDA kernels or XLA. You have contributed to open source projects like PyTorch, JAX, MLX or similar. You care about research outcomes as much ...

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 ...

architectures, including cross-architecture deployability and strict QoS timing constraints. Familiarity with High-Performance Computing (HPC), NVIDIA GPU acceleration, and hardware optimization (e.g., CUDA, TensorRT). Native fluency in Linux, Docker, and CI/CD pipelines—you know how to deploy and scale headless simulations unattended. Experience building ...

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 ...

experience working as a Senior Software Engineer with deep expertise in both Python and low-level programming (e.g. C/C++, Rust, assembly or CUDA). A history of direct contributions to vLLM or similar high-performance open-source ML/AI projects (e.g. PyTorch, Hugging Face TGI, TensorRT ...

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 ...

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 ...

Excel/Google Sheets or Python modelling experience) to forecast system behaviour Optimisation of code running on GPUs and/or other accelerators (e.g. CUDA) Solid understanding of computer architecture fundamentals and how LLMs and Deep Learning models execute on that hardware (inference vs. training, matrix multiplication, KV-caching ...

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 ...

knowledge of SOLID principles, OOD and software design patterns Security clearance will be needed Desirable Experience - Embedded Software Engineer -Southampton MATLAB OpenGL or Vulkan CUDA/OpenCL FPGA development and HDL #J-18808-Ljbffr ...

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 ...

PyTorch ecosystem Experience with inference optimisation techniques, including quantisation, speculative decoding and model parallelism across modern GPU architectures Strong software engineering skills, including Python, CUDA and building reliable systems for machine learning workloads Strong communication skills, with the ability to collaborate across research, infrastructure and engineering teams Why join ...

Some Linux administration; understanding setup for HPC middleware. Nice to Haves: 5+ years HPC application experience Experience building and running HPC applications on GPU. CUDA or OpenACC or OpenMP paradigms. Experience running AI models on CPU or GPU. Any experience understanding/inspecting/writing assembly Understanding of memory ...

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 ...

recruitment. Building engineering teams through hiring, onboarding, mentoring or capability development. Open-source development or large software projects with complex dependencies. Vulkan, OpenCL, CUDA, DirectX, Metal or similar graphics and compute APIs. Machine learning frameworks, inference runtimes or model tooling. CI/CD, CMake, cross-compilation, packaging or developer ...

recruitment. Building engineering teams through hiring, onboarding, mentoring or capability development. Open‐source development or large software projects with complex dependencies. Vulkan, OpenCL, CUDA, DirectX, Metal or similar graphics and compute APIs. Machine learning frameworks, inference runtimes or model tooling. CI/CD, CMake, cross‐compilation, packaging or developer ...

/20), delivering robust, scalable, and maintainable solutions. Develop and optimize compute-intensive algorithms using multithreading, SIMD techniques, and GPU acceleration technologies such as CUDA and OpenCL. Analyze software performance, identify computational bottlenecks, and implement optimizations across CPU and GPU architectures. Leverage AI-assisted engineering tools such as GitHub ...

automation and orchestration systems for these platforms Proficiency in a low-level language such as C, C++, or Rust and in GPU frameworks like CUDA Competence in front-end web design to allow easy interfacing with large datasets Our Culture Follow the science. We prioritise rigorous scientific inquiry, relying ...

fixed.* Drive platform integration: Help partners adopt and optimize NVIDIA GPUs, systems, networking, and software libraries across their development pipelines. This may include CUDA, CUDA-X, NCCL, TensorRT-LLM, NeMo, Transformer Engine, CUTLASS, vLLM, SGLang, and related technologies.* Influence NVIDIA’s platform roadmap: Work with NVIDIA hardware … frontier AI research, model development, training, post-training, inference, and emerging AI workloads.* Practical understanding of GPU platforms and AI software libraries, including CUDA, CUDA-X, NCCL, PyTorch or JAX, and relevant training or inference systems.* Experience with large-scale GPU clusters, high-speed networking, distributed storage, workload ...