51 to 75 of 133 CUDA Jobs in England

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 ...

Python and PyTorch; you write clean, experimental code and iterate fast. JAX is acceptable with strong Python proficiency. C++ and Rust are not required, CUDA and GPU knowledge is expected but hands-on experience is not required. Research experience of some form: a thesis, publications, a dedicated research project ...

infrastructure and containerised environments. A track record of taking research code from prototype to robust, reusable infrastructure that other people actually use. Bonus experience: CUDA/Triton kernel development; FlashAttention-style attention implementations; experience with foundation models for biology, vision, or language; contributions to open-source ML frameworks. Personally ...

communication. Nice to have Contributions to KServe, vLLM, SGLang or adjacent inference, gateway or orchestration projects. Experience modifying engine internals, profiling kernels or diagnosing CUDA and collective-communication issues. Experience with mixture-of-experts models, expert parallelism, speculative decoding or disaggregated serving. Experience routing by data-sensitivity policy, evaluation ...

meetings and events. Resourceful, collaborative, and comfortable taking ownership in a high‐performance startup. Nice to have Deep knowledge of vendor SDKs such as CUDA, ROCm, Vela, or Vitis AI. Experience with edge CPUs, GPUs, and NPUs, including Jetson, Raspberry Pi, Snapdragon, or Arm platforms. Linux, Docker ...

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). If this ...

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 ...

reasoning, collaboration, and communication with trading researchers. Intellectual curiosity, originality, practical judgement, and reliable availability. Useful experience: high-performance computing, distributed large-model training, CUDA or ROCm optimisation, end-to-end model development, and ML research/tooling/infrastructure best practices. International candidates are encouraged to apply. Jump ...

range of hardware from resource constrained embedded systems through to cloud computing is desirable. As is any knowledge of GPU programming languages and frameworks (CUDA, ROCm, etc). Your future colleagues will be similarly highly skilled, with experience across industry and the drive to innovate. You will find yourself ...

through evaluation. Desirable Skills & Experience Experience training, fine-tuning or optimising foundation models. Experience with large-scale distributed training and experimentation. Experience with JAX, CUDA or other high-performance ML tooling. Publications at leading machine learning conferences or journals. Contributions to open-source machine learning or reinforcement learning projects. ...

Cloud Hypervisor, QEMU). Tell us what broke and how you fixed it. Systems depth: Linux internals (namespaces, cgroups, virtualisation), GPU drivers and the CUDA stack, networking and storage. 3+ years in systems or infrastructure engineering. Substantial research and open-source engineering count. AI leverage. Demonstrable custom agentic workflows ...

performance and low-level optimisation: reasoning about memory, compute and latency at the device level, and optimising performance across kernels, compilers and hardware (e.g. CUDA, Triton or equivalent). Production inference systems: hands-on experience building and hardening real-time, low-latency prediction pipelines in high-performance environments. Numerics ...

these — as long as you\'re open to learning, please apply. Backend: Python Frontend: TypeScript and React Deployment: Kubernetes Infrastructure: GCP Machine learning: PyTorch, CUDA, Ray Why Encord Competitive salary, commission, and meaningful equity in a high-growth startup Strong in-person culture — most of the team works from ...

/or PyTorch Experience of software development in Python, Rust, C/C++, or a similar language Experience monitoring and optimising code written in CUDA, ROCm, OpenCL, or similar Experience monitoring and optimising LLM deployments with 50+ billion parameters Experience working with stakeholders across multiple teams What We Offer ...

turn them into shipped features Contribute to platform design decisions, take part in design reviews and help us hire Work with Python, PyTorch, CUDA, Kubernetes and GCP/AWS Who we're looking for An owner. You take ambiguous product needs, make the architecture calls and carry the work ...

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 ...

token prediction, or other inference acceleration methods. Experience with agentic workloads, including tool calling, structured outputs, streaming APIs, high concurrency, and multi-step orchestration. CUDA or Triton familiarity, even if the role is not primarily a kernel-engineering role. Open-source contributions to vLLM, SGLang, TensorRT-LLM, FlashInfer, LMCache ...

deployments, monitoring and alerting stacks, and hardware acceptance and regression testing. Deep familiarity with the NVIDIA technology stack, including HGX platforms, NVLink/NVSwitch, CUDA-level debugging, and NCCL performance tuning. Strong leadership skills with the ability to set technical direction, solve complex problems, and guide engineering teams. Excellent ...

related inference acceleration methods. Experience supporting agentic workloads involving tool calling, structured outputs, streaming APIs, high concurrency, and multi‐step orchestration. Familiarity with CUDA or Triton; the role does not require kernel engineering to be the candidate’s primary specialization. Contributions to open‐source projects such as vLLM, SGLang ...

Medusa, multi-token prediction, orrelatedinference acceleration methods. Experiencesupporting agentic workloads involvingtool calling, structured outputs, streaming APIs, high concurrency, and multi-step orchestration. Familiarity with CUDA or Triton; the role does not require kernel engineering to be the candidate’s primary specialization. Contributions to open-source projects such asvLLM, SGLang ...

numerical simulation codes on local, national and international (US/CAN/EU) HPC clusters using AMD and/or NVIDIA GPUs (e.g., via CUDA, HIP, OpenCL, or similar). Carrying out application profiling and benchmarking, and contributing technical cases and support to group proposals for acquiring more ...

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 ...

PyTorch, Triton, and advanced scheduling tools like Kubernetes or Ray. Ideal candidates bring 3+ years in AI infrastructure, strong Python skills, and hands-on CUDA/C++ experience, with a degree in CS/EE/Applied Math. #J-18808-Ljbffr ...

small, highly technical team. Experience that would stand out Game engines, graphics, rendering, CAD, computational geometry, simulation, robotics, or scientific software. GPU programming, CUDA, or other performance‐sensitive computing. Integrating components written in different languages. Taking research‐led software into production. A personal interest in hardware, engineering, or building ...

/or PyTorch Experience of software development in Python, Rust, C/C++, or a similar language Experience monitoring and optimising code written in CUDA, ROCm, OpenCL, or similar Experience monitoring and optimising LLM deployments with 50+ billion parameters Experience working with stakeholders across multiple teams What We Offer ...