26 to 50 of 51 Kubeflow Jobs in the UK

infrastructure security, reliability and operational best practice. Desirable Experience The following would be advantageous: MLOps or LLMOps experience. Experience with platforms such as SageMaker, Kubeflow or ZenML . Extensive on-premises Kubernetes deployment experience. Prometheus or comparable observability platforms. AWS Karpenter. AWS Compute Optimizer. Experience operating highly distributed systems. Familiarity ...

infrastructure security, reliability and operational best practice. Desirable Experience The following would be advantageous: MLOps or LLMOps experience. Experience with platforms such as SageMaker, Kubeflow or ZenML . Extensive on-premises Kubernetes deployment experience. Prometheus or comparable observability platforms. AWS Karpenter. AWS Compute Optimizer. Experience operating highly distributed systems. Familiarity ...

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 ...

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 ...

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 ...

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 ...

individual model work. Strong software engineering fundamentals - you build reliable, well-tested, maintainable systems. Python, Kotlin/Java, SQL. Experience with ML orchestration (Airflow, Kubeflow, or equivalent), model registries (MLflow or similar), and container-based deployment End-to-end understanding of the ML lifecycle - data ingestion through training, packaging, serving ...

infrastructure. Good proficiencyin 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 engineering ...

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/ ...

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, deep learning, and personalisation for potential integration into existing systems Требования Strong demonstrated experience with ML training frameworks, mainly TFX and Kubeflow Pipelines SDK, and model serving technologies such as TensorFlow Serving, Triton, and TorchServe Expertise in the full machine learning lifecycle, from model development, deployment, and serving ...

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 ...

e.g., Scikit-learn, TensorFlow, PyTorch). Experience with cloud platforms (AWS, GCP, or Azure) for ML. Strong knowledge of MLOps principles and tools (e.g., Kubeflow, SageMaker, MLflow). Ability to work with large datasets and distributed systems. Sample Work Required: Please provide a case study or documentation for a previous ...

traditional physics solvers (OpenFOAM/Simcenter) into ML pipelines for active learning and model refinement. Setup \"physics-aware\" CI/CD and experiment tracking (Kubeflow/MLFlow) that validates physical consistency laws. Skills/Must have Orchestration: Expert-level Kubernetes (AKS/EKS) is essential. ML Frameworks: Strong proficiency ...

gapped deployment experience. Experience building self-serve ML platforms or tools for non-expert users. Experience with lakeFS , DVC , MLflow , Weights & Biases , Kubernetes, Kubeflow, Flyte, Dagster, Airflow, or Argo. LLM application, context engineering, structured output, or LLM evaluation experience. Exposure to radar, AIS, EO/IR fusion, tracking, sensor fusion ...

improvement. Familiarity with Model Context Protocol (MCP) for tool interoperability, plus Google ADK, LangGraph/LangChain for agent orchestration and multi‐agent patterns. Ray, Kubeflow, or similar frameworks. Experience embedding controls, audit evidence, and governance in regulated environments. Experience with GPU efficiency, autoscaling strategies, and workload right‐sizing. About working ...

ambiguous environments Enjoys solving complex technical problems collaboratively Nice-to-Haves Experience with large scale model training or distributed inference systems Familiarity with Ray, Kubeflow, Slurm, or similar distributed scheduling platforms Experience with InfiniBand, RDMA, or high-performance networking Experience operating bare metal infrastructure Familiarity with storage systems commonly used ...

Engineering, and Managed Services on cloud and on prem AI/ML & MLOps - Open source AI/ML solutions, AIOps automation, model lifecycle management, Kubeflow, MLFlow, KServe, and AI infrastructure on cloud and edge IoT - Ubuntu on embedded devices and/or edge servers, device management, and robotics Cloud - Ubuntu ...

ixolabs.ai is seeking an MLOps Engineer for AI training to build scalable pipelines, registries, and rollback plans. You will review code across Kubeflow, MLflow, SageMaker, Vertex AI & Azure ML and improve CI/CD for ML workflows. Ideal candidates bring multiple cloud ML platform strengths, Docker/Helm proficiency ...

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 #CIBAppliedAI #J ...

Well versed and proven experiencein 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/ ...

scalable performance. You will partner with Data Science, Actuarial, and Product teams to deliver impactful tooling. Responsibilities include building deployment and monitoring tooling, maintaining Kubeflow environments, and delivering production-grade Python applications while communicating effectively with technical and non-technical #J-18808-Ljbffr ...

following would be valuable, but is not required: Go, Rust, C/C++, or Python. Kubernetes and containerised infrastructure. Argo, OSMO, Temporal, Ray, Kubeflow, or similar systems. GPU clusters or large-scale AI infrastructure. High-performance computing. Simulation, robotics, autonomous systems, or Physical AI. Programming language or compiler research. Performance ...

Role Who you are Strong demonstrated experience using ML Training frameworks (mainly TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe) Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance Proficiency in Python and knowledge … libraries/frameworks (e.g., TensorFlow, PyTorch) Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe) Experience with high-volume data processing and real-time streaming architectures Strong understanding of recommendation system design and personalisation algorithms Familiarity with Generative ...

Learning to define and evolve Relation’s platform strategy. Our platform spans on-premises infrastructure and public cloud environments, supporting computational scientist notebooks through Kubeflow, model training and serving, internal services and genomic pipelines. You will set the technical direction across these areas, build and develop the team responsible … alongside experience operating infrastructure across hybrid on-premises and cloud environments. Experience building, running or evolving MLOps infrastructure, ideally including notebook environments such as Kubeflow, GPU compute for distributed training and model serving. Familiarity with batch compute for data-intensive scientific workloads, with an understanding of the reliability, scalability ...