51 to 75 of 82 Kubeflow Jobs in London

Familiarity with transformer architectures and practical handling of LLM context, prompt chaining, and prompt engineering. Hands-on experience with MLOps tools like MLflow, Weights & Biases, and orchestration platforms like Kubeflow or Databricks. Deep understanding of cloud platforms (especially Azure and AWS), containers, microservices, and event-driven architecture. Strong problem-solving and debugging skills, including debugging AI pipelines and multi-model More ❯

home-based role, we are hiring worldwide. What your day will look like Understand Ubuntu, Linux, networking and services in real-world environments Architect cloud infrastructure solutions like Kubernetes, Kubeflow, OpenStack, Ceph, and Spark either On-Premises or in Public Cloud (AWS, Azure, Google Cloud) Architect and integrate popular open source software such as PostgreSQL, MongoDB, Kafka, Cassandra and NGINX More ❯

partner with data scientists, software engineers, and product managers. Nice-to-Haves: Experience with streaming platforms and understanding stream/table transformations. Familiarity with ML system deployment and management (Kubeflow, MLflow, Airflow, Flyte, etc.). Knowledge of monitoring, alerting, and operational best practices for data-intensive systems. Experience with Feature Stores or similar ML data management tools. What We Offer More ❯

machine learning. Strong experience with deep learning using TensorFlow. Experience implementing scalable, distributed, and highly available systems using Google Could Platform. Experience with Google AI Platform/Vertex AI, Kubeflow and Airflow. Proficient in Python. Java or Scala is a plus. Experience in data processing using SQL and PySpark. Experience working with foundation models and other GenAI technologies Desired Characteristics More ❯

with version controls systems (e.g. Git) Desirables: Experience with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data in data warehouses Desire to build interpretable and explainable ML models (using techniques such as SHAP) Desire to More ❯

with version controls systems (e.g. Git) Desirables: Experience with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data in data warehouses Desire to build interpretable and explainable ML models (using techniques such as SHAP) Desire to More ❯

with the right to work and able to be in the office 2–3 days per week Nice to Have Background in healthcare, clinical tech, or MLOps tooling (MLflow, Kubeflow, Vertex Pipelines) What’s on Offer 💸 Competitive salary + meaningful equity 🧘‍♂️ 25 days holiday + UK bank holidays 🌱 Flexible hours and a sustainable work pace 🌇 Bright, collaborative office minutes from More ❯

with the right to work and able to be in the office 2–3 days per week Nice to Have Background in healthcare, clinical tech, or MLOps tooling (MLflow, Kubeflow, Vertex Pipelines) What’s on Offer 💸 Competitive salary + meaningful equity 🧘‍♂️ 25 days holiday + UK bank holidays 🌱 Flexible hours and a sustainable work pace 🌇 Bright, collaborative office minutes from More ❯

with the right to work and able to be in the office 2–3 days per week Nice to Have Background in healthcare, clinical tech, or MLOps tooling (MLflow, Kubeflow, Vertex Pipelines) What’s on Offer Competitive salary + meaningful equity ‍♂️ 25 days holiday + UK bank holidays Flexible hours and a sustainable work pace Bright, collaborative office minutes from More ❯

platform engineering teams to identify technical gaps, scope backend development efforts, and deliver core platform capabilities such as: Model training orchestration CI/CD for ML (e.g., using MLflow, Kubeflow, or Vertex AI Pipelines) Model versioning, monitoring, and governance Enable high-impact AdTech use cases including: Marketing Mix Modeling (MMM) Real-time personalization and bidding Audience segmentation and targeting Predictive More ❯

platform engineering teams to identify technical gaps, scope backend development efforts, and deliver core platform capabilities such as: Model training orchestration CI/CD for ML (e.g., using MLflow, Kubeflow, or Vertex AI Pipelines) Model versioning, monitoring, and governance Enable high-impact AdTech use cases including: Marketing Mix Modeling (MMM) Real-time personalization and bidding Audience segmentation and targeting Predictive More ❯

platform engineering teams to identify technical gaps, scope backend development efforts, and deliver core platform capabilities such as: Model training orchestration CI/CD for ML (e.g., using MLflow, Kubeflow, or Vertex AI Pipelines) Model versioning, monitoring, and governance Enable high-impact AdTech use cases including: Marketing Mix Modeling (MMM) Real-time personalization and bidding Audience segmentation and targeting Predictive More ❯

with backend and platform engineering teams to identify technical gaps, scope backend development efforts, and deliver core platform capabilities such as: CI/CD for ML (e.g., using MLflow, Kubeflow, or Vertex AI Pipelines) Model versioning, monitoring, and governance Enable high-impact AdTech use cases including: Marketing Mix Modeling (MMM) Real-time personalization and bidding Audience segmentation and targeting Predictive More ❯

This range is provided by Franklin Bates. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range Direct message the job poster from Franklin Bates Supporting growth of technology More ❯

Months Ship V1 of the food-analysis API (image + text → nutrient vector → protocol tag) with < 1 s latency. Stand-up an ML Ops stack (Vertex AI/Kubeflow, Terraform-managed infra) that supports rapid retraining and audit logs. Scale the team—hire or upskill research engineers, data scientists and backend developers; formalise career ladders and a high-trust culture. More ❯

of products includes on-premise cloud solutions such as Openstack, MicroCloud and Ceph, and solutions that could be deployed either on-premises or in public clouds such as Kubernetes, Kubeflow, Spark, PostgreSQL, etc. The team works hands-on with the technologies by deploying, testing and handing over the solution to our support or managed services team at the end of More ❯

Join a world-leading cybercrime SaaS organisation in an exciting Senior/Principal AI Engineer role to deliver robust and impactful AI-based solutions to advance threat detection efficiency. Our client is headquartered in the UK and, whilst being well More ❯

Join a world-leading cybercrime SaaS organisation in an exciting Senior/Principal AI Engineer role to deliver robust and impactful AI-based solutions to advance threat detection efficiency. Our client is headquartered in the UK and, whilst being well More ❯

Join a world-leading cybercrime SaaS organisation in an exciting Senior/Principal AI Engineer role to deliver robust and impactful AI-based solutions to advance threat detection efficiency. Our client is headquartered in the UK and, whilst being well More ❯

About Netcraft Netcraft is the global leader in cybercrime detection and disruption. We're a trusted partner for three of the four largest companies in the world and many large country governments. We've blocked more than 200 million malicious More ❯

environments UK-based and available to work 2–3 days per week in-office (London) Bonus Points Experience in healthcare, medtech, or clinical systems Familiarity with MLOps tooling (MLflow, Kubeflow, Vertex Pipelines More ❯

environments UK-based and available to work 2–3 days per week in-office (London) Bonus Points Experience in healthcare, medtech, or clinical systems Familiarity with MLOps tooling (MLflow, Kubeflow, Vertex Pipelines More ❯

environments UK-based and available to work 2–3 days per week in-office (London) Bonus Points Experience in healthcare, medtech, or clinical systems Familiarity with MLOps tooling (MLflow, Kubeflow, Vertex Pipelines More ❯

skills to effectively convey technical information and ideas at all levels, building trust with stakeholders. Preferred qualifications, capabilities, and skills Experience in designing and implementing pipelines using DAGs (e.g., Kubeflow, DVC, Ray). Ability to construct batch and streaming microservices exposed as gRPC and/or GraphQL endpoints. Demonstrable experience in parameter-efficient fine-tuning, model quantization, and quantization-aware More ❯

skills to effectively convey technical information and ideas at all levels, building trust with stakeholders. Preferred qualifications, capabilities, and skills Experience in designing and implementing pipelines using DAGs (e.g., Kubeflow, DVC, Ray). Ability to construct batch and streaming microservices exposed as gRPC and/or GraphQL endpoints. Demonstrable experience in parameter-efficient fine-tuning, model quantization, and quantization-aware More ❯