5 of 5 Remote/Hybrid Kubeflow Jobs in the UK

environments. Collaborate with Data Scientists and Engineers to productionise models. Improve platform scalability, reliability, and automation. Key Skills Strong Python experience. MLOps tooling (MLflow, Kubeflow, SageMaker, or similar). Docker and Kubernetes. CI/CD tooling (GitHub Actions, GitLab CI, Azure DevOps). Cloud platforms (AWS, Azure, or GCP). ...

agentic workflows Experience with Google Cloud Platform (Vertex AI, BigQuery) or an equivalent major cloud ML platform Familiarity with ML tooling such as MLflow, Kubeflow or SageMaker, plus Docker and Kubernetes Comfortable working in a fast-moving, resource-conscious environment where you learn on the job and scope can shift ...

estimation. Multi-object localisation or multi-modal perception systems. GPU optimisation, CUDA, inference acceleration or 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 ...

equivalent practical experience. Familiarity with our core stack, with strong experience in at least two of: Python, TypeScript, relational databases, APIs, Docker, Kubernetes, Kubeflow, AWS. Strong core software engineering and DevOps skills, including CI/CD, version control, containerisation, and cloud deployment. A solid grasp of engineering best practice, producing ...

solutions. Lead integration of compute, storage, networking, the AI software stack (CUDA, ROCm, Triton, NIM, NVIDIA AI Enterprise, Run:ai, Slurm, Kubernetes/Kubeflow) and managed-service operating models across multiple domains, delivery units and geographies. Build business cases, TCO and unit-economics models (cost per token, cost per training … knowledge of the AI software and orchestration stack: CUDA, cuDNN, NCCL, ROCm, Triton Inference Server, NIM, vLLM, TensorRT-LLM, Slurm, Kubernetes (with GPU Operator), Kubeflow, Run:ai, MLflow and NVIDIA AI Enterprise. Familiarity with datacenter facilities engineering for AI workloads: high-density power, liquid cooling (DLC, rear-door, immersion ...