14 of 14 Permanent Kubeflow Jobs in London

Docker. Strong understanding of CI/CD principles and DevOps best practices. Experience supporting highly available, scalable production environments. Nice to have: Experience with Kubeflow and ML platform tooling. Exposure to AI, machine learning or GenAI projects. Experience with observability tooling such as Prometheus, Grafana or OpenTelemetry. Experience working within ...

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 Have constructed batch and streaming microservices exposed as REST/gRPC endpoints Experience with container orchestration tools (e.g. Kubernetes, Helm ...

demonstrated ability to write clear documentation and collaborate across engineering teams. Ecosystem Knowledge : Hands‐on experience supporting software delivery and MLOps tooling (e.g., Kubernetes, Kubeflow, MLflow, Triton, Docker, or SageMaker/Azure ML). Equal Opportunity Statement We are committed to fostering and promoting an inclusive professional environment ...

demonstrated ability to write clear documentation and collaborate across engineering teams. Ecosystem Knowledge : Hands-on experience supporting software delivery and MLOps tooling (e.g., Kubernetes, Kubeflow, MLflow, Triton, Docker, or SageMaker/Azure ML) Equal Opportunity Statement We are committed to fostering and promoting an inclusive professional environment ...

programming and visualisation languages and libraries (SQL, python, matplotlib, etc.) as well as some of the supporting tools and platforms (e.g. git, MLFlow, Kubernetes, Kubeflow, Trino, AirFlow). A strong understanding of statistical concepts (hypothesis testing, sampling, probability distributions). Excellent communication and collaboration skills to effectively bridge ...

Jupyter, Pandas, Scikit Learn, Matplotlib) Strong software development skills (Python is the preferred language) Proven experience in deploying ML/AI services suing Kubernetes & KubeFlow Strong management and leadership skills – previous experience managing a team Strong influencing, communication and stakeholder management skills Be Customer Focused – constantly improving our customers’ experience ...

engineering skills in Python, with experience building scalable services, APIs, and production-quality code Experience with modern ML tooling and platforms (e.g.Databricks,MLflow, Airflow, Kubeflow, SageMaker, Vertex AI) Familiarity with CI/CD pipelines and infrastructure-as-code (e.g.Terraform, CloudFormation) Experience building robust, maintainable, and testable ML pipelines and APIs ...

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 ML, or Vertex AI). Generative AI: LLM fine-tuning (LoRA/QLoRA), RAG architecture … code: Terraform and Ansible for repeatable, automated provisioning of GPU clusters and AI platform environments; GitOps (ArgoCD) for continuous, declarative platform delivery. Pipeline orchestration: Kubeflow Pipelines, Apache Airflow, or Argo Workflows to orchestrate multi-stage training, fine-tuning, and inference pipelines. Cluster & workload scheduling: Slurm, Run:ai, and NVIDIA Base ...

based application development (AWS & Azure). Familiarity with one or more ML frameworks and technologies: scikit‐learn, xgboost, TensorFlow, PyTorch, Spark, SageMaker, Vertex AI, Kubeflow, Seldon, Triton. Strong communication skills, able to express ideas clearly and collaborate across teams. #J-18808-Ljbffr ...

well-tested production code Desirable Experience Any exposure to the following would be beneficial: MLflow, Weights & Biases or similar experiment tracking tools Airflow, Prefect, Kubeflow or similar workflow orchestration platforms Kubernetes GPU-based workloads Time-series or telemetry data Distributed model training Edge, on-premise or resource-constrained deployments Industrial ...

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 ...

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 ...

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 Level ...

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you ...