26 to 41 of 41 Kubeflow Jobs in the UK

Machine Learning Engineer. Technical Skills: Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib). Data transformation & manipulation : experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex AI (developing ML services). Expertise: Solid understanding of computer science fundamentals and time-series forecasting. Machine Learning: Strong ...

Nice to Have Experience managing physical data centres, co‐location facilities, or hybrid infrastructure environments. Working knowledge of ML orchestration frameworks (e.g., Ray, Slurm, Kubeflow). Background in media pipelines, VFX tooling, or media compliance standards (MPA, ISO 27001). Prior experience working in a hybrid startup/scale ...

application development (we use AWS & Azure)Familiarity with one or more ML frameworks and technologies: scikit-learn, xgboost, TensorFlow, PyTorch, Spark, SageMaker, Vertex AI, Kubeflow, Seldon, TritonStrong communication skills, able to express ideas clearly and collaborate across teamsAdditional InformationBring all of you to workWe create the conditions for high performers ...

clients Expertise in implementing SSO across a variety of industry standard software Preferred/Bonus Experience with MLOps/LLMOps (Softwares such as Sagemaker, Kubeflow or ZenML). Deployment of on‐premise Kubernetes Prometheus (or other stacks) observability Experience with AWS Karpenter & Compute Optimizer Compliance literacy - ISO 27001, NIST SSDF ...

APIs, running both on cloud and on-prem environments. The tech stack you will use for this includes: Python, PyTorch, Pandas, fastAPI, Scipy, Kubeflow, among others. Mentor and develop engineers and data scientists; provide technical direction and clear, calm decision‐making under pressure. Travel to customer sites in North America ...

VertexAI TOOLS & TECHNOLOGIES Languages: Python, SQL Data & Transformation: dbt, Snowflake, BigQuery Visualisation & BI: Looker Engineering & MLOps: Docker, GitHub Workflow & Orchestration: Vertex AI Pipelines (GCP), Kubeflow LLMs & GenAI: Gemini API, Claude API INTERVIEW PROCESS Step 1: People Team Screening Call (30 min) Step 2: Hiring Manager Call: Experience (45 min) Step ...

required: AWS Kubernetes IaC (Terraform) GitOps (Helm, ArgoCD) Monitoring and alerting for production systems (Prometheus/Grafana or similar) Azure (desirable) MLOps in k8s (Kubeflow etc) Running GPU workloads on K8s (drivers, scheduling, utilisation) Familiarity with AI engineering Experience deploying in air-gapped customer environments Experience with secrets management ...

models - model versioning, experiment tracking, and deployment workflows. Work with data science teams to configure MLOps tooling such as Vertex AI, MLflow, Kubeflow, or similar platforms. Enable automated model retraining, drift detection, and performance monitoring pipelines. #J-18808-Ljbffr ...

equivalent practical experience. Familiarity with our core stack, with strong experience in at least 2 components: 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. Knowledgeable on engineering best practices and comfortable with ...

levels; convey information clearly and create trust with stakeholders. Preferred qualifications, capabilities, and skills Experience designing/implementing pipelines using DAGs (e.g. Kubeflow, DVC, Ray) Experience of big data technologies (e.g. Spark, Hadoop) Have constructed batch and streaming microservices exposed as REST/gRPC endpoints Familiarity with GraphQL We recognize ...

ideas at all levels; convey information clearly and create trust with stakeholders.Preferred qualifications, capabilities, and skillsExperience designing/implementing pipelines using DAGs (e.g. Kubeflow, DVC, Ray)Experience of big data technologies (e.g. Spark, Hadoop)Have constructed batch and streaming microservices exposed as REST/gRPC endpointsFamiliarity with GraphQL#CIBAppliedAIJ.P. Morgan ...

generations and topologies. Exposure to MLOps tooling and AI platform layers: experiment tracking (MLflow, W'B), model serving frameworks (Triton, vLLM), and pipeline orchestration (Kubeflow, Airflow). Familiarity with InfiniBand and high-performance networking as it relates to distributed training performance — sufficient to engage credibly with network and infrastructure teams ...

versed and proven experience in programming languages such as Python, Java, or C++. Experience with data pipeline and workflow management tools (e.g., Apache Airflow, Kubeflow). Strong problem-solving skills and ability to work in a fast-paced environment. Excellent communication and collaboration skills. Longstanding experience in AI/ ...

metadata stores). ML workflow orchestration and serving: Operate the systems researchers use to launch experiments, data jobs, and production endpoints — workflow engines (e.g., Kubeflow Pipelines, Airflow), GPU schedulers (e.g., Volcano, Slurm), experiment trackers (e.g., MLflow, Weights & Biases), and managed‐inference platforms (e.g., Modal, Triton) — and maintain a launcher … analytical (e.g., BigQuery, Snowflake), and embedded (e.g., SQLite) stores; and object storage with caching layers. Familiarity with ML workflow orchestration and experiment tracking (e.g., Kubeflow Pipelines, MLflow). Experience with monitoring and observability tooling (e.g., Prometheus/Grafana, OpenTelemetry) and CI/CD for infra and ML workflows (e.g., GitHub ...

years of experience in technical solution delivery and project management. 3 years of experience with AI/ML Infrastructure (e.g., GPUs, GKE, EKS, Kubernetes, Kubeflow). Experience using Bash. Preferred qualifications: Master's degree or PhD in Computer Science, Engineering or a related field. Experience developing and tuning AI/ ...

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 ...