1 to 25 of 35 Kubeflow Jobs in the UK

with Generative AI and LLM deployment patterns. A proven history of reducing cloud spend on large-scale AI clusters. Experience with tools like MLflow, Kubeflow, LangSmith, or Phoenix. Expertise in AWS/GCP/Azure cost tools, Kubecost, or Cloudability. Extensive background of Kubernetes (K8s), Docker, and service meshes. Expert ...

cloud-native production environments. Demonstrated experience managing compute-intensive GPU infrastructure and high-performance computing (HPC) environments. Advanced proficiency in Kubernetes (K8s), Docker, Helm, KubeFlow, and service meshes (e.g., Istio). Hands-on experience with Terraform, Ansible, GitHub Actions, ArgoCD, or Jenkins. Experience with vLLM, Ray, MLflow, LangChain/LangSmith ...

skills and attention to detail Experience with LLMs and generative AI (OpenAI, Hugging Face, LangChain) Knowledge of NLP or computer vision Experience with MLflow, Kubeflow or similar MLOps tools What We Offer ✓ Competitive salary based on experience ✓ Diverse AI projects across multiple industries ✓ Collaborative and research-driven team environment ...

Studio, OpenAI, AKS), GCP (Vertex AI, Cloud Run), AWS (Bedrock, SageMaker)* Experience building and automating AI/ML pipelines using tools such as MLflow, Kubeflow, Azure ML, Vertex Pipelines, Airflow or Google ADK* Hands-on experience with Generative and Agentic AI frameworks such as LangChain, LlamaIndex, CrewAI, Autogen, Google ...

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 ...

APIs, scripts and CI/CD automationWorking knowledge of modern MLOps stacks including experiment tracking and artifact managementHands-on experience with orchestration tools (e.g., Kubeflow, Apache Airflow, Metaflow or Prefect)Demonstrated skills with Docker, Kubernetes and distributed deploymentsPractical knowledge of Infrastructure-as-Code (Terraform) and a major cloud provider ...

Ability to analyse large datasets and communicate insights effectively. Experience with LLMs, generative AI, and prompt engineering. Knowledge of MLOps tools and frameworks (MLflow, Kubeflow, Airflow). Familiarity with SQL, NoSQL, and distributed data technologies. Experience deploying AI models in production environments. Publications, patents, or open-source contributions ...

teams. Desirableskills andexperience: Experience building platforms or applications that support Data Science, Machine Learning, or AI workloads. Experience with MLOps tooling such as MLflow, Kubeflow, Vertex AI, or similar technologies. Knowledge of workflow orchestration platforms such as Apache Airflow. Experience with data processing technologies such as Pandas, Apache Beam, Spark ...

Ability to analyse large datasets and communicate insights effectively. Experience with LLMs, generative AI, and prompt engineering. Knowledge of MLOps tools and frameworks (MLflow, Kubeflow, Airflow). Familiarity with SQL, NoSQL, and distributed data technologies. Experience deploying AI models in production environments. Publications, patents, or open-source contributions ...

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 ...

integrating heterogeneous data sources into governed pipelines. Familiarity with model monitoring, version control, experiment tracking, and reproducibility tooling such as MLflow, Weights & Biases, DVC, Kubeflow, or similar. Experience working cross-functionally with data scientists, domain experts, and operational teams to move models into production. Strong communication skills and the ability ...

Proven experience designing and deploying ML systems in production (5+ years in relevant roles) Proficiency in Python and SQL, and orchestration tools (Airflow, Kubeflow, Dagster, etc.) Experience with modern cloud platforms (preferably GCP or AWS), Kubernetes, and CI/CD workflows Understanding of ML model lifecycles: training, validation, deployment ...

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 ML, or Vertex AI).Generative AI: LLM fine-tuning (LoRA/QLoRA), RAG architecture design … 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 Command Manager ...

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 ...

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 ...

including real-time serving, feature stores, autoscaling, and blue/green deployments Strong Python and SQL skills Hands-on GCP experience, especially Vertex AI, Kubeflow pipelines, and BigQuery — or strong fluency on an equivalent cloud with a clear ability to get to Vertex fast Solid CI/CD and production ...

RayServe, Triton, vLLM, or similar) with real latency and cost constraints(preferred RayServe) MLOps pipeline tooling - training pipelines, model registries, feature stores, and lineage (Kubeflow, MLflow, Feast, Weights & Biases, or equivalents) LLMOps in production - inference serving, prompt/version management, and LLM observability (tracing, evals, drift, guardrails, cost per request ...

infrastructure. Proficiency 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. Proven experience in AI/ML infrastructure engineering ...

infrastructure. Good proficiency 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. Significant experience in AI/ML infrastructure ...

DAST practices. Automation and scripting skills with Bash, Python or Go. Strong communication and stakeholder management skills. Desirable MLOps or LLMOps experience (SageMaker, Kubeflow, ZenML). Prometheus or other observability tooling. AWS Karpenter and Compute Optimizer experience. Knowledge of ISO 27001, NIST or OWASP frameworks. Experience working within Defence ...

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 ...

/CD pipelines, MLOps frameworks, and automated machine learning deployment processes Hands-on experience with Azure Databricks or similar machine learning platforms (ie MLFlow, KubeFlow, SageMaker etc) Experience building APIs, microservices, and cloud-based solutions that integrate machine learning capabilities into wider platforms and applications Excellent collaboration and technical communication ...

with Data Science, Actuarial, and Product teams. Responsibilities: Build and support ML lifecycle tooling for model deployment, monitoring, and alerting Maintain and improve the Kubeflow environment for Data Scientists and Actuaries Create pricing analytics tools to accelerate impact analysis and reduce manual work Collaborate with pricing and product teams ...

Machine Learning Engineer Programming 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 grasp ...