101 to 125 of 133 CUDA Jobs in England

Inference Engineer to join our growing team in the UK. You will optimize and scale our inference engine for latency and cost budgets, spanning CUDA kernels, Rust serving runtime, and Python model code. You should have hands-on experience with GPU programming, production distributed systems, and familiarity with ...

week. Experience for the Senior GPU Software Engineer includes: 5+ years of software engineering experience with significant GPU or high-performance computing experience Strong CUDA and GPU programming experience Excellent C++ programming skills Strong understanding of CPU/GPU interaction and data movement #J-18808-Ljbffr ...

does not. Thrive in ambiguous, early-stage environments where defining the problem is part of the job. Strong candidates may also have: CUDA or equivalent low-level accelerator programming. Compression, information theory, or model quantisation experience. Background in timing-based protocols, proofs of space or time, or distance bounding. ...

infrastructure. ORCA PT Series quantum systems are room temperature and rack-mounted which connect directly to GPU clusters via NVIDIA's CUDA-Q platform, enabling accelerated AI workloads delivering advantages over traditional silicon-based systems. Backed by a strong portfolio of patent families spanning photonic integrated circuits, quantum memory … maintain documentation and tutorials. Lead the development of ORCA's integrations with other quantum and classical software tools and frameworks, such as NVIDIA's CUDA-Q, PyTorch and JAX. Provide escalation support for ORCA's Customer Success team leading root-cause analysis, communicating clearly with customers and internal stakeholders ...

simulations, and data-intensive applications. Support cluster bring-up and optimization, including OS provisioning, workload managers (e.g., Slurm), container platforms, and GPU software stacks (CUDA, drivers, AI frameworks). Provide advanced troubleshooting and performance tuning across compute, GPU, storage, and networking subsystems. Perform on-site or remote deployment support … system stack. Experience working across customers, sales, and engineering/manufacturing teams. Preferred Skills Knowledge of AI/HPC software stacks such as CUDA, Kubernetes, Slurm, Docker, and AI frameworks like PyTorch/TensorFlow. Experience designing or deploying AI training clusters or large-scale HPC environments. Exposure to liquid ...

CommonAI CIC is seeking a GPU Kernel and Performance Engineer to accelerate research models on real hardware, primarily NVIDIA GPUs. You will join a compact team turning new model designs into efficient GPU code, measuring ...

Inference Engineer to define and build how we serve AI workloads at scale, reporting to the CTO. You’ll own the layer above CUDA/GPU work, shaping inference delivery, throughput, and reliability as we scale data-centre compute for energy applications. With 4+ years in large-scale inference ...

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 ...

resources. Integrate ML models into production systems where latency matters. Work across a mix of programming languages: C/C++/Python/CUDA and other low-level GPU languages. Build large scale ML systems that are observable, performant, and flexible. Help improve productivity by reducing the iteration cycle … Proficiency in Pytorch, JAX, Tensorflow or other DL library. Ability to thrive in a collaborative, team-oriented environment Expertise in GPU or Accelerator programming (CUDA, Triton, SYCL, ROCm or equivalent) Experience building ML systems at large scale (hundreds of TBs of training data, low latency or high throughput inference ...

Fuse Energy is seeking a seasoned CUDA performance engineer to design and optimise kernels for high-throughput workloads in a high-performance compute environment. You will profile GPU bottlenecks, build tooling to align power draw with energy pricing, and optimise multi-GPU scaling across NCCL/MPI. Collaboration with ...

across GPUs, CPUs, and accelerators to maximize training throughput and minimize latency. You will implement fused kernels, leverage tensor cores, and push Triton/CUDA capabilities, while collaborating on distributed multi-node deployment and performance instrumentation. #J-18808-Ljbffr ...

principal) Architectures distribuées : microservices, API gRPC Middleware : Apache Pulsar, RabbitMQ Cloud : AWS Stockage HPC : Lustre (ou équivalent) Réseaux (atout) : RDMA, libfabric GPU (connaissances appréciées) : CUDA, architecture mémoire Profil recherché Expérience significative en développement de systèmes distribués Maîtrise de Rust, ou forte capacité à monter en compétence rapidement Solide compréhension ...

experience in JavaScript, TypeScript, and Python, including developing web applications; experience in C/C++, or with GPU and 3D rendering libraries (such as CUDA, WebGL or Three.js), is an advantage. Experience working with databases; experience with both SQL and NoSQL (e.g. MongoDB) databases is desirable. Experience developing software … research environment, in a range of applications/technologies Experience implementing software in C/C++ Experience working with GPU, e.g., OpenGL, Vulkan, CUDA, WebGL or browser-based 3D rendering libraries (e. g. Three.js) Experience in both SQL and NoSQL (e.g. MongoDB) databases Implementing scientific or algorithmic software ...

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 ...

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 Rust ...

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. ...

Game engines render the world for human eyes. This team renders it for a complex defence system. You’ll write C++ and GPU code (CUDA, OpenGL or Vulkan) that simulates how radar and electro-optical sensors see targets, terrain and atmosphere. It has to be physically accurate, and fast … work in both. What you’ll need Essential: Strong, practical C++ development experience Hands-on GPU programming with at least one of CUDA , OpenGL or Vulkan A working understanding of the physics behind RF or EO/IR propagation and sensing, and experience turning physical models into software Good ...

sensor and peripheral outputs into existing C++ algorithms and processing pipelines. Develop interfaces between hardware acquisition software and existing application/algorithm code. NVIDIA CUDA/GPU Develop, integrate and optimise software using NVIDIA CUDA where appropriate. Understand the Jetson GPU architecture and its implications for application performance. ...

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 ...

develops. We care more about how well you understand hardware and memory than about ML research credentials. What You'll Do Write and optimise CUDA and Triton kernels on NVIDIA GPUs for sparse and structured model components, including block-sparse matrix operations and attention variants. Adapt and extend open … components to them where it is useful. Contribute improvements back to open-source projects where possible. Proven experience writing and optimising GPU kernels in CUDA or Triton, ideally on recent NVIDIA architectures. A strong understanding of GPU architecture and memory hierarchies (e.g. shared memory, HBM bandwidth, memory coalescing, occupancy ...

distillation, speculative decoding, KV-cache reuse, KV-cache compression, long-context inference, MoE routing, and model/runtime co-optimization. Build prototypesusingPyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks,and collaboratewith MLEs and platform engineers toturn them intoproduction components. Research LLM request routing and scheduling strategies, including cache … OSDI, SOSP, ISCA, orHPCA. Experience deploying ML models or inference optimizations in production. Experience with vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo, FlashAttention, FlashInfer, Triton, CUDA, or PyTorch internals. Experienceapplyingpost-training, SFT, DPO, RLHF, RLAIF, preference optimization, or synthetic data generation to inference quality or efficiency. Open-source research artifacts ...

machine: design and implement the software that models the full lifecycle of a physical host from discovery, inference bring-up to GPU driver/CUDA stack, health validation, and decommission/RMA — as explicit, versioned states and transitions. Build the self-service API: design declarative APIs and a control …/IPMI, BMC) and/or networking fundamentals (VLANs, BGP, fabric design), or GPU/accelerator infrastructure. Experience with GPU cluster software stacks (NCCL, CUDA, InfiniBand/RoCE). Prior work at a hyperscaler, GPU cloud, or datacenter-scale infrastructure organization. Systems programming in Rust or Go. About Together ...

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 ...

Quadrants is an open-source translation layer that turns ordinary Python into optimized machine code at runtime, across CPU (Arm64, x86) and GPU (AMDGPU, CUDA, Metal, Vulkan) backends. CUDA is the primary target, with x86 the strong runner-up, especially for real-time simulation. The others drive adoption ...

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 ...