1 to 25 of 166 NVIDIA Jobs in England

LLMOps• Hands-on with MLOps platforms (Azure ML, Databricks, SageMaker) and vector/retrieval databases (Pinecone, Milvus, pgvector)• Experience with GPU-accelerated infrastructure and NVIDIA AI Enterprise or equivalent stacks• Exposure to fine-tuning, RLHF, or SLM distillation is a strong plusCloud-Native & Infrastructure• Deep expertise in Kubernetes and container ...

utilisation, reliability, and cost-efficiency. Your Impact Provision and manage cloud-native AI/ML infrastructure utilising Kubernetes, Docker, and GPU orchestration frameworks (e.g., NVIDIA GPU Operator, Slurm, or Ray). Automate core platform infrastructure using Infrastructure as Code (IaC) tools like Terraform, Helm, and Ansible. Optimise GPU compute workloads ...

/ML/CS or related field. Beneficial knowledge General tooling and platforms: Databricks, AWS, GCP, GitHub, Docker/Kubernetes, MLflow, Jira. Edge deployments: Nvidia Jetson (e.g. AGX Orin), Raspberry Pi, or other embedded accelerators. Distributed model training & infra: Pytorch DDP, FDSP and TorchTitan, Megatron, Slurm, Run:ai, DeepSpeed, Kubernetes ...

dive when necessary Desirable Exposure to computational research involving GPU, including AI/ML methods applied to biomedical problems Experience supporting GPU‐accelerated workloads, NVIDIA tooling, CUDA‐aware environments, and/or AI/ML and bioinformatics workloads on shared compute platforms. Familiarity with bioinformatics or scientific workflow frameworks (e.g. ...

edge AI. Real-time computer vision systems. Docker, Kubernetes, Kubeflow or MLOps pipelines. Aerial, satellite or ISR imagery. Synthetic data generation, Unreal Engine or NVIDIA Omniverse. Distributed training and large-scale model optimisation. Defence, government or national security projects. An MSc or PhD in Computer Vision, Artificial Intelligence, Machine Learning ...

/Kubernetes models, including LLM inference. Proficiency in Infrastructure as Code (IaC) tools like Terraform or Ansible. Experience with GPU acceleration technologies (e.g., NVIDIA CUDA) in containerized environments. Familiarity with monitoring tools such as Prometheus and Grafana. Exceptional communication and problem-solving skills with a client-focused mindset. Excellent client ...

designs, processes and systems. Nice to Have AI/ML workloads, GPU-accelerated systems, or HPC infrastructures, including GPU partitioning with MIG and the NVIDIA GPU Operator. Experience with RDMA fabrics such as InfiniBand or RoCEv2, and GPUDirect data paths. High-throughput distributed storage at scale, such as Ceph ...

related STEM discipline. Senior Software Engineer- DV Security Cleared- Desirable Technical Experience Experience with some of the following technologies would be highly beneficial: NVIDIA CUDA/GPU-accelerated computing Machine learning and data analytics NumPy/SciPy, PostgreSQL/SQLite, Docker/containerised environments Ansible, Cython, Celery/Redis JavaScript ...

related STEM discipline. Senior Software Engineer- DV Security Cleared- Desirable Technical Experience Experience with some of the following technologies would be highly beneficial: NVIDIA CUDA/GPU-accelerated computing Machine learning and data analytics NumPy/SciPy, PostgreSQL/SQLite, Docker/containerised environments Ansible, Cython, Celery/Redis JavaScript ...

systems. Nice to Have Expertise in AI/ML workloads, GPU-accelerated systems, or HPC infrastructures, including GPU partitioning with MIG and the NVIDIA GPU Operator. Experience with RDMA fabrics such as InfiniBand or RoCEv2, and GPUDirect data paths. High-throughput distributed storage at scale, such as Ceph ...

with Platform Engineering/Platform SRE to fully support both our infrastructure and platform stacks. Willingness to cross train with HPC Engineering, supported by NVIDIA to enhance our HPC supportability offering Requirements 5+ Years Proven experience in globally scaled, performance-intensive environments operating to a 24/7 support model ...

with Platform Engineering/Platform SRE to fully support both our infrastructure and platform stacks. Willingness to cross train with HPC Engineering, supported by NVIDIA to enhance our HPC supportability offering What you bring 5+ Years Proven experience in globally scaled, performance-intensive environments operating to a 24/ ...

record leading technical delivery (not just advisory) on enterprise-scale AI or HPC infrastructure programmes. AI Hardware & Data Center Infrastructure GPU/accelerator architectures: NVIDIA/AMD, including multi-node scale-out design. Accelerator interconnects: NVLink, NVSwitch High-performance networking: InfiniBand and RoCEv2 fabric design, 400G/800G Ethernet, rail … frameworks: PyTorch and TensorFlow at a working, hands-on level. Distributed training: Horovod, DeepSpeed, Megatron-LM, or equivalent multi-node training frameworks. Inference & serving: NVIDIA Triton, vLLM, TensorRT-LLM, or equivalent high-throughput serving platforms. MLOps/LLMOps: Kubeflow, MLflow, and at least one hyperscaler ML platform (SageMaker, Azure ...

have Experience building and operating large‐scale observability systems across multiple data centers. Experience monitoring GPU clusters and AI/ML workloads, including NVIDIA DCGM and training or inference performance metrics. Deeper experience with hardware and network telemetry, such as IPMI/Redfish, NetFlow/sFlow, SNMP, gNMI, or eBPF. ...

expect one person to bring experience in every area.* You may also bring experience with emerging technologies such as NeRFs, Gaussian Splatting, NVIDIA Omniverse, Unity or Unreal, or knowledge of model explainability, open-source licensing or CI/CD-based testing of robotics and machine learning pipelines. These are helpful ...

expect one person to bring experience in every area. You may also bring experience with emerging technologies such as NeRFs, Gaussian Splatting, NVIDIA Omniverse, Unity or Unreal, or knowledge of model explainability, open-source licensing or CI/CD-based testing of robotics and machine learning pipelines. These are helpful ...

Haves Experience troubleshooting, provisioning, or operating bare-metal server infrastructure. Experience operating or troubleshooting GPU, HPC, or other high-performance compute infrastructure. Familiarity with NVIDIA GPUs, DCGM, InfiniBand, RoCE/RDMA, NVLink, or high-speed data center networking. Experience with hardware management and provisioning technologies such as PXE, BMC, IPMI ...

expect one person to bring experience in every area. You may also bring experience with emerging technologies such as NeRFs, Gaussian Splatting, NVIDIA Omniverse, Unity or Unreal, or knowledge of model explainability, open‐source licensing or CI/CD‐based testing of robotics and machine learning pipelines. These are helpful ...

networking for AI/HPC workloads, including InfiniBand and/or RoCE. Experience with subnet managers and fabric orchestration technologies such as OpenSM or NVIDIA UFM. Expert-level understanding of modern data centre routing and control planes, including BGP, EVPN-VXLAN, and Clos/spine-leaf architectures. Production experience with ...

concurrent opportunities across a geographic territory. Fluency in English required; proficiency in 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 ...

TensorFlow, PyTorch, scikit-learn) Experience with cloud platforms (e.g., Azure AI, AWS SageMaker, Google Cloud AI) Experience with Private cloud platforms (HPE Private AI, Nvidia AI Enterprise, Dell AI Factories) Understanding of data engineering practices (ETL, data lakes, big data tools like Spark). Knowledge of designing scalable, distributed systems. ...

TensorFlow, PyTorch, scikit-learn) Experience with cloud platforms (e.g., Azure AI, AWS SageMaker, Google Cloud AI) Experience with Private cloud platforms (HPE Private AI, Nvidia AI Enterprise, Dell AI Factories) Understanding of data engineering practices (ETL, data lakes, big data tools like Spark). Knowledge of designing scalable, distributed systems. ...

TensorFlow, PyTorch, scikit-learn) Experience with cloud platforms (e.g., Azure AI, AWS SageMaker, Google Cloud AI) Experience with Private cloud platforms (HPE Private AI, Nvidia AI Enterprise, Dell AI Factories) Understanding of data engineering practices (ETL, data lakes, big data tools like Spark). Knowledge of designing scalable, distributed systems. ...

playing a key role in 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 ...

communication and stakeholder management skills, able to work closely with Platform, Network, and leadership. Nice to Have Experience in HPC or GPU‐accelerated environments (NVIDIA GPUs, InfiniBand/RDMA, parallel file systems). Scripting skills in Python and/or Bash for automation and tooling. Understanding of performance tuning ...