101 to 125 of 128 CUDA Jobs in the UK

Proxima is seeking a Principal ML Performance Engineer to optimize training and inference for structural and generative models, with a focus on CUDA, Triton, and distributed training across large GPU clusters. You will profile bottlenecks, write efficient kernels, and drive multi-node scalability. As a senior leader, you will ...

advancing AI and engineering best practices. Day-to-day tasking can include: Working on high-throughput vision systems on NVIDIA Jetson hardware, involving; CUDA/TensorRT acceleration Multi-modal (thermal + optical) sensors Robust real-time tracking Exploring AI Assurance and AI Safety Delivering technical expertise on a variety … Skills: We are interested in the following skills, but they are not essential for you to apply: Knowledge of C++, Python, PyTorch, OpenCV, CUDA, TensorRT, Git, WSL, Docker, Jira/Confluence Machine Learning and Deep Learning Computer Vision methodologies and algorithms MLOps Developing AI for use on Edge Computers ...

engineers who have: A track record of working on model training or model inference at scale , or on low‐level GPU coding (e.g. CUDA, Triton). Experience with one is great, multiple is even better. What will I be doing? As a Senior AI Infrastructure Engineer focused on model … Model training (especially transformers and LLMs). Model inference at scale (again, especially transformers and LLMs). Low‐level GPU work , such as writing CUDA or Triton kernels. Comfortable working in production environments at meaningful scale (traffic, data, or organizational). You communicate clearly, can explain complex technical topics ...

engine behind every Perplexity query and deploy dozens of model architectures at scale with tight latency and cost budgets. Our stack is Rust, Python, CUDA, and CuTe DSL.### ### **Responsibilities:*** **New models support.** Support transformer-based retrieval, text-generation, and multimodal models in our inference infrastructure, from weight loading … request scheduling and KV-cache management to support in API Gateway.* **GPU kernels migration to CuTe DSL.** Port our in-house CUDA kernels to NVIDIA's CuTe DSL so they run on GB200 today and are portable to Vera Rubin racks tomorrow.* **Rust-native serving runtime.** Develop our internal ...

Full-time ML engineering role building financial-ML frameworks, HPC training pipelines, low-latency inference, and large-scale GPU systems with Python, C++, CUDA, and modern ML libraries. Build reusable frameworks for financial machine learning. Optimise training pipelines for high-performance computing. Integrate ML models into latency-sensitive production … systems. Build large-scale, observable ML systems. Work with C, C++, Python, CUDA, and other low-level GPU technologies. Python and/or C++. PyTorch, JAX, TensorFlow, or another deep-learning library. GPU programming with CUDA, Triton, SYCL, ROCm, or similar tools. Large-scale ML systems, including very ...

systems, storage, fabric, MLOps stack and managed services — to land service-led AI solutions. Lead integration of compute, storage, networking, the AI software stack (CUDA, ROCm, Triton, NIM, NVIDIA AI Enterprise, Run:ai, Slurm, Kubernetes/Kubeflow) and managed-service operating models across multiple domains, delivery units and geographies. …/NVSwitch fabrics, congestion control and fabric design for rail-optimised and fat-tree topologies. Working knowledge of the AI software and orchestration stack: CUDA, cuDNN, NCCL, ROCm, Triton Inference Server, NIM, vLLM, TensorRT-LLM, Slurm, Kubernetes (with GPU Operator), Kubeflow, Run:ai, MLflow and NVIDIA AI Enterprise. Familiarity ...

Profile and optimize training and inference for structural and generative models, including transformers, diffusion, and geometric deep learning Write and tune custom kernels (CUDA, Triton) and use compilers (torch.compile, TensorRT, XLA) when beneficial Scale distributed training across 32-64 nodes, employing FSDP, DeepSpeed, tensor and pipeline parallelism, and mixed … selecting infrastructure, influencing research teams, and mentoring engineers Deep knowledge of PyTorch internals with hands-on experience profiling and fixing real bottlenecks Experience with CUDA and Triton, skilled at reading Nsight output, and strong understanding of memory bandwidth and occupancy Experience with distributed training at multi-node scale Strong ...

About Huawei Research and Development UK Limited Founded in 1987, Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. We have 207,000 employees and operate in over ...

hack or compromise. Everything is Python-first and runs anywhere. Kernels are written once, and Quadrants, our in-house JIT compiler, lowers them to CUDA, AMD ROCm, Apple Metal, Vulkan, x86, and ARM64. A single laptop or a datacenter. Massively batched GPU simulation for learning at scale, and complex … cost. You will work closely with Quadrants. At ease debugging across the full platform matrix: Windows, Linux, and macOS, on x86 and arm64, over CUDA, AMD, and Apple Metal (and possibly Intel XPU via Vulkan soon) Open-source reflexes: triaging issues, reviewing external pull requests, communicating with a community. ...

scientific policy engagement, grant processes, or national/European research program structures. Experience with NVIDIA's stack for visual and multimodal AI, built on CUDA and CUDA-X, including Cosmos world foundation models, NeMo Framework and Megatron for multimodal model training, multimodal Nemotron methodology, Isaac robotics platform, NuRec ...

scientific policy engagement, grant processes, or national/European research program structures. Experience with NVIDIA's stack for visual and multimodal AI, built on CUDA and CUDA-X, including Cosmos world foundation models, NeMo Framework and Megatron for multimodal model training, multimodal Nemotron methodology, Isaac robotics platform, NuRec ...

business, and it will be challenging: this is a field with no easy or obvious solutions. Qualifications Strong engineering skills, especially any of: CUDA/Triton/Pallas/CuTe DSL kernel development, lower-level PyTorch/JAX/XLA development, CUDA Graphs, FPGA/ASIC experience Must ...

operate in significantly outpaces what we can currently build, meaning speed to power and reliability are critical to how we scale. This puts CUDA/GPU performance engineering at the center of how Fuse scales its compute infrastructure. Responsibilities Design, implement, and optimise CUDA kernels for high-throughput … baselines and drive continuous performance improvements. Contribute to internal libraries, documentation, and best practices for GPU performance engineering. 4+ years of experience writing production CUDA code, or equivalent strong project/industry experience. Deep understanding of GPU architecture (SMs, warps, memory hierarchy, occupancy). Proficiency in C++ and CUDA ...

leadership for software and multi-disciplinary engineering teams, drives innovation in products and services, and influences strategic technology direction. Leveraging deep expertise in C++, CUDA, Linux systems, kernel and user-space development, the role solves complex technical challenges, mentors engineers, and collaborates across functions to deliver high-quality, high … relevant experience in a similar role (~8 years) with the ability to add value with limited development Experience Strong knowledge and demonstrable experience of CUDA and C++ Hands‐on experience in working within a structured engineering environment that includes: Requirements Analysis/Definition Design/Implementation Defect Tracking Testing ...

Design, build, and optimize distributed training systems (PyTorch) for multi-node GPU clusters, ensuring scalability, robustness, and high utilization Implement efficient low-level code (CUDA, cuDNN, Triton, custom kernels) and integrate it seamlessly into high-level training frameworks Optimize workloads for hardware efficiency: CPU/GPU compute balance, memory … Bring Deep experience in distributed systems, ML infrastructure, or high-performance computing (8+ years) Production-grade expertise in Python Low-level performance mastery: CUDA/cuDNN/Triton, CPU-GPU interactions, data movement, and kernel optimization Scaling at the frontier: experience with PyTorch and training jobs using data, context ...

optimising how power‐dense GPU workloads are scheduled, cooled, and balanced against grid conditions in real time. We're looking for a CUDA Engineer to write and optimise the low‐level GPU code that powers our inference workloads. You'll design custom CUDA kernels, tune performance across memory … operate in significantly outpaces what we can currently build, meaning speed to power and reliability are critical to how we scale. This puts CUDA/GPU performance engineering at the center of how Fuse scales its compute infrastructure. Responsibilities Write and optimise custom CUDA kernels for core transformer ...

sources of electricity demand, Fuse is expanding into high-performance compute infrastructure at the intersection of energy and AI. We're looking for a CUDA Engineer to write and optimise the low-level GPU code that powers our inference workloads: designing custom CUDA kernels, tuning performance across memory … squeezing maximum throughput out of every GPU in our fleet, working at the level of SMs, warps and memory hierarchies. ResponsibilitiesWrite and optimise custom CUDA kernels for core transformer inference operationsProfile kernels to identify and eliminate bottlenecks in occupancy, memory throughput and warp divergenceApply kernel fusion to reduce memory ...

demand, Fuse is expanding into high-performance compute infrastructure that sits at the intersection of energy and AI. We're building the GPU/CUDA performance layer and the inference serving layer at the same time, from scratch -- and we're looking for the founding engineer … Founding AI Inference Engineer to define and build how Fuse serves AI inference workloads at scale, reporting directly to the CTO. Where our CUDA and GPU engineering hires own kernel-level and hardware performance, this role owns the layer above it: how models actually get served, scaled, and delivered ...

electricity demand, Fuse is expanding into high-performance compute infrastructure at the intersection of energy and AI. We're building the GPU/CUDA performance layer and the inference serving layer at the same time, from scratch, and we're looking for the founding engineer to own the latter. … serving, deciding where and how to apply quantisation, distillation, speculative decoding and similar techniques to improve throughput and cost per token, partnering with the CUDA/GPU engineersMake the core software architecture calls on serving frameworks and orchestration (e.g. vLLM, TensorRT-LLM, SGLang, Triton Inference Server or equivalents)Translate ...

electricity demand, Fuse is expanding into high-performance compute infrastructure at the intersection of energy and AI. We're building the GPU/CUDA performance layer and the inference serving layer at the same time, from scratch, and we're looking for the founding engineer to own the latter. … serving, deciding where and how to apply quantisation, distillation, speculative decoding and similar techniques to improve throughput and cost per token, partnering with the CUDA/GPU engineers Make the core software architecture calls on serving frameworks and orchestration (e.g. vLLM, TensorRT-LLM, SGLang, Triton Inference Server or equivalents ...

Keysight Technologies is seeking a Senior Staff GPU Engineer to lead software development across the full product lifecycle, focusing on high-performance CUDA/C++ on Linux. You will mentor teams, shape technical direction, and deliver world-class solutions in PNT and related areas. The role demands deep hardware ...

write the kernels and operations that get the most out of the hardware. This is deep performance work: fused kernels, tensor cores, Triton and CUDA, distributed multi-node deployment. It fits someone with expert GPU-optimization skills and a deep understanding of transformer internals. … home in CUDA, Triton, and profilers, this is the wrong depth. What You'll Own Profile and optimize GPU/CPU/accelerator code for maximum utilization and minimal latency. Write high-performance PyTorch, Triton, and CUDA, dropping to custom operations when needed. Develop fused kernels and leverage ...

about efficient large-scale training, low-latency inference in real-time systems and high-throughput inference in research. Part of this is improving straightforward CUDA, but the interesting part needs a whole-systems approach, including storage systems, networking and host- and GPU-level considerations. Zooming in, we also want … end. Low-level GPU knowledge of PTX, SASS, warps, cooperative groups, Tensor Cores and the memory hierarchy. Debugging and optimisation experience using tools like CUDA GDB, NSight Systems, NSight Compute-sight-systems and nsight-compute. Library knowledge of Triton, CUTLASS, CUB, Thrust, cuDNN and cuBLAS. Intuition about the latency ...

platforms. This is a fantastic opportunity for an experienced Senior Software Engineer to work on technically challenging problems across compilers, GPU architectures, CUDA, LLVM and high-performance computing. Experience for the Senior Software Engineer includes: Strong C++ software engineering experience A strong academic background, ideally from a Russell Group … university Experience working with low-level software and complex systems Desired: CUDA, Compilers If you are a Senior Software Engineer looking for a technically challenging role working close to the hardware and at the intersection of C++, compilers and GPU technology, then please apply today to learn more. ...

Design and optimize distributed inference systems on GPU clusters, pushing throughput with large-batch serving and efficient resource utilization Implement efficient low-level code (CUDA, Triton, custom kernels) and integrate it seamlessly into high-level frameworks Optimize workloads for both throughput (batching, scheduling, quantization) and latency (caching, memory management … performance serving (8+ years) Production-grade expertise in Python, with strong background in systems languages (C++/Rust/Go) Low-level performance mastery: CUDA, Triton, kernel optimization, quantization, memory and compute scheduling Proven track record scaling inference workloads in both throughput-oriented cluster environments and latency-critical ...