51 to 75 of 94 CUDA Jobs in the UK

must, or you have previous experience training models (strong math skills are still required). Strong PyTorch experience. Strong ability to code in Rust, CUDA, or C (with a preference for Rust). Solid understanding of Transformers (not the movies). A product mindset. you’ll be building things ...

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 ...

plus; a strong background in mathematics is required. Alternatively, experience training models with strong math skills. Strong coding ability in Rust (preferred), CUDA, or C. Solid understanding of transformer architectures. A product mindset; you’ll build production‐ready products. Hybrid Remote with the London Office. What ...

libraries, or custom kernels/fused ops. Experience with multi-node cluster orchestration (Slurm, Ray, Kubernetes, or similar). Comfort debugging performance issues across CUDA/NCCL, networking, IO, and data pipelines. Experience working with containerized environments (Docker, Singularity/Apptainer). A track record of building tools that ...

from the crowd: Entrepreneurial demeanor A track record leading teams whose work shows up in software revenue and renewals. Familiarity with Omniverse, NIM, NeMo, CUDA‐X, DGX, or AI Factory architectures, and standing across EMEA enterprise customers, partners, field, and product teams. Real passion for mentoring senior people ...

evolve the compute stack. The role shapes platform evolution and enables researchers to push the boundaries of machine learning. You will work with Python, CUDA, Kubernetes, and deep learning frameworks like PyTorch, applying #J-18808-Ljbffr ...

systems, collaborating with software, product management and research teams. You will require BS+10y or MS+7y in CS/ML/Robotics, expert Python and CUDA/PyTorch skills, and a track record in computer vision and model fine-tuning. #J-18808-Ljbffr ...

apply advanced techniques, optimize training pipelines on HPC clusters, and integrate ML models into latency-sensitive production environments, using C/C++, Python, and CUDA across large-scale systems. #J-18808-Ljbffr ...

systems for quantitative finance. You will optimize training pipelines, deploy models to low-latency production environments, and work across C/C++, Python, CUDA, and related GPU technologies. Join a fast-paced, collaborative team focused on impactful projects that push the boundaries of AI research and its applications ...

front and centre. Strong candidates may also have Experience with a systems programming language like Rust or C++. Experience with writing and profiling CUDA kernels. A track record of building reliable research tools. Why this is interesting You’ll shape the core technical foundation of a frontier ...

vision concepts including segmentation, pose estimation, and embeddings. Experience building production ML systems and inference pipelines. Strong Python engineering skills. Experience with GPU optimisation, CUDA fundamentals, TensorRT, or ONNX is advantageous. Experience in fashion, e-commerce, creative tooling, gaming avatars, or virtual try-on is highly desirable. Additional InformationBeneFITS ...

training (fine‐tuning, alignment, reward modelling). Publications at top‐tier AI conferences such as ICML, ICLR, NeurIPS, CVPR, etc. Experience using HPCs and CUDA for training large‐scale models. The ability to translate research into a product vision and carry it through to delivery. Nice to have Computer ...

practical product impact and close collaboration with product teams. The role requires a strong math background, expertise in PyTorch, and experience with Rust/CUDA for high-performance inference. This is a unique opportunity to shape the AI strategy for a fast-growing platform. #J-18808-Ljbffr ...

purely academic backgrounds. Full-stack depth: distributed training frameworks such as Megatron-LM, DeepSpeed or FSDP, GPU performance work, and experience down to the CUDA, Triton or XLA level. Contributions to open-source ML frameworks or research codebases. They genuinely value this. Strong software engineering habits. Clean code, good ...

optimize the end-to-end ML stack: data pipelines, training loops, inference serving, and deployment. Design and implement GPU-accelerated components, including custom CUDA kernels where off-the-shelf libraries are not enough. Work closely with the founders to translate product requirements into concrete optimization goals and technical roadmaps. ...

SDKs, APIs, or platforms that other engineers depend on. Experience developing for inference hardware and/or GPUs (e.g. one year or more using CUDA or ROCm). A good understanding of modern ML workloads and the practical challenges of deploying large language models to production. An instinct ...

deep learning models in PyTorch (not just using high-level tooling).Strong proficiency with at least one relevant stack/toolchain (e.g. TensorRT, CUDA, Qualcomm QNN, Triton, OpenCL) and confidence learning adjacent frameworks quickly.Comfort operating at multiple levels of abstraction — from high-level model behaviour down to low-level ...

deep learning models in PyTorch (not just using high‐level tooling). Strong proficiency with at least one relevant stack/toolchain (e.g. TensorRT, CUDA, Qualcomm QNN, Triton, OpenCL) and confidence learning adjacent frameworks quickly. Comfort operating at multiple levels of abstraction — from high-level model behaviour down ...

. Nice to have:• Product experience in datacentre hardware, cloud infrastructure, HPC, AI platforms, or security/compliance products. • Familiarity with GPU ecosystem concepts (CUDA awareness, GPU memory constraints, interconnects, training vs. inference economics). • Understanding of private AI solution patterns and components (RAG, vector databases, model serving, evaluation ...

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 ...

system installation, performance tuning, and troubleshootingExpertise in troubleshooting distributed GPU workloadsDeep knowledge around GPU optimization and performance Proficiency in Python scripting and automation frameworks CUDA or C/C++ experience is a plusExperience with NVIDIA technologies beyond CUDA, such as NCCL, GPUDirect RDMA, and NVLink Familiarity with configuration ...

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 ...

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 ...

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems—across high-stakes industries like finance, manufacturing, defense, healthcare, and ...

Research Engineer Cambridge or London, UK (100% Onsite) Our client is a global leader in semiconductor innovation, developing advanced technologies that power billions of smart devices worldwide. With significant investment in artificial intelligence research, the ...