1 to 25 of 179 NVIDIA Jobs in England

Cloud technologies: AWS primarily Azure and GCP beneficial Virtualisation and Containerisation Containerisation (e.g. Docker, Podman) Container management (e.g. Kubernetes) Experience in GPU containerisation (e.g. NVIDIA Container Toolkit, Run:AI) Architectural styles Microservices Serverless Edge compute APIs (both RESTful and Protobuf GRPC) Stream based pub/sub systems (including Kafka ...

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 ...

such as Pure Storage or Dell EMC Cisco Nexus and ACI VMware Cloud Foundation Terraform, Ansible, or similar automation technologies CCNP or equivalent certification NVIDIA certifications or AI infrastructure experience DevOps, automation, and orchestration tools Python, REST APIs, and Git Docker and Kubernetes Knowledge of modern CPU, GPU, and infrastructure ...

architectures, specifically implementing Intel Secure Boot and Arm TrustZone. Engineer reliable software connectivity and data pipelines between Intel host boards and Eizo (ARM/NVIDIA) GPGPUs. Design and integrate Intelligent Platform Management Interface (IPMI) solutions for robust hardware management. Implement Ubuntu and relevant driver infrastructure Technical Operations Author and maintain ...

LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the Role We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers ...

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 ...

gaps and taking initiative as needed to help the team win together. Nice‐to‐Haves Experience with our Edge AI stack. Experience with the NVIDIA edge ecosystem (Jetson Orin, DeepStream SDK, TensorRT) is a huge plus. Video Technologies. Familiarity with video pipelines, GStreamer, or ffmpeg. Fleet management. Experience with tools ...

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/ ...

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 ...

Metaflow, or Argo Workflows. Experience with containerisation and infrastructure tooling such as Docker, Kubernetes, or Terraform.Experience profiling or optimising ML systems, for example using NVIDIA Nsight. Understanding of ML workflows and researcher experience, even if you are not focused on model development. What we're not looking for This ...

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 ...

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 ...

still being developed Strong Preference For Experience integrating accelerator hardware (GPUs, FPGAs, ASICs, NPUs, or novel architectures) into customer inference workflows Familiarity with the NVIDIA inference stack - CUDA, TensorRT, Triton Exposure to disaggregated inference architectures, prefill/decode separation, or KV cache management Compensation & Benefits Highly Competitive Salary ...

seamless integration 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 ...

What you will do Training Infrastructure Design and operate distributed training infrastructure for neural operator architectures (Transolver, Point Cloud Transformer, etc.) on our large NVIDIA DGX B200 platform. Optimize training pipelines for throughput, fault tolerance, and cost efficiency, including checkpointing strategies, gradient accumulation, and multi-node synchronization. Build and maintain ...

pressure environment. Master's or PhD in Engineering, Physics, Computer Science, Mathematics, or a related scientific discipline (or equivalent practical experience). Experience with NVIDIA PhysicsNemo or similar physics-informed machine learning frameworks. Knowledge of fluid dynamics concepts and CFD data analysis. Experience in motorsport, Formula 1, or aerospace aerodynamics. ...

work and good attention to detail with an imaginative approach to problem solving. The ability to work independently with minimal supervision. Desirable: Experience using NVIDIA Jetson or similar AI computing platforms. Wireless communications such as Bluetooth, WLAN, cellular, low-power radio. Wired communications such as CAN, RS232, RS485 ...

systems for UAVs using ROS and simulation environments (e.g. Gazebo or IsaacSim) Have experience integrating edge compute (e.g. Raspberry Pi 5 + AI or Nvidia Jetson) to a UAV Integrate sensors and actuators for improved drone perception and navigation Knowledge of control systems, computer vision, and machine learning Conduct testing ...

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 ...

environment. Master's or PhD in Engineering, Physics, Computer Science, Mathematics, or a related scientific discipline (or equivalent practical experience). Desirable Experience with NVIDIA PhysicsNemo or similar physics-informed machine learning frameworks. Knowledge of fluid dynamics concepts and CFD data analysis. Experience in motorsport, Formula 1, or aerospace aerodynamics. ...

most advanced high-performance computing infrastructure. As a Cloud Support Engineer, you will support cutting-edge GPU and CPU platforms — including the latest NVIDIA architectures — powering dense, large-scale compute environments used for AI, machine learning, and next-generation workloads. This is an opportunity to build expertise at the forefront ...

seamless integration 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 ...