1 to 25 of 82 Kubeflow Jobs in London

Familiarity with on-device or edge-AI deployments (e.g., TensorFlow Lite, ONNX, mobile/embedded inference). Knowledge of MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar) for experiment tracking and model governance. Open-source contributions or published papers in top-tier AI/ML conferences (NeurIPS, ICML, CVPR, ACL More ❯

machine learning models in production. Knowledge of big data technologies like Hadoop, Hive, or Spark. Familiarity with MLOps tools and practices, such as MLflow, Kubeflow, or DataRobot. Education: Bachelor’s degree in Computer Science, Software Engineering, or related field (or equivalent practical experience). Why Join Us? Work on cutting More ❯

Python, experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI). What we offer Culture of caring: At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every More ❯

Python, experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI). What we offer Culture of caring: At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every More ❯

Python, experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI). What We Offer Culture of Caring: At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every More ❯

real-time data processing (Kafka, Kinesis, Flink) Knowledge of containerization and infrastructure-as-code (Docker, Kubernetes, Terraform) Familiarity with MLOps practices and tools (MLflow, Kubeflow, etc.) Experience with data governance frameworks and data cataloging Understanding of graph databases and unstructured data processing Knowledge of advanced analytics techniques and statistical methods More ❯

reliability engineering Strong expertise in multi-cloud and hybrid infrastructure including AWS, GCP, and on-premises environments Experience with MLOps tooling such as MLFlow, Kubeflow, DataRobot, or similar platforms for ML lifecycle management Experience with containerization and orchestration (Docker, Kubernetes) specifically for ML workloads and GPU clusters Deep understanding of More ❯

platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Hands-on experience with CI/CD pipelines, version control, and ML workflows (MLflow, Kubeflow). Proven track record of delivering ML models that solve real-world business challenges at scale. Excellent communication skills with the ability to work effectively More ❯

platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Hands-on experience with CI/CD pipelines, version control, and ML workflows (MLflow, Kubeflow). Proven track record of delivering ML models that solve real-world business challenges at scale. Excellent communication skills with the ability to work effectively More ❯

control, CI/CD pipelines, and test-driven development. Nice to Have: Experience within financial services or fintech. Familiarity with MLOps tools (e.g., MLflow, Kubeflow, SageMaker). Understanding of regulatory or compliance frameworks. Academic background in mathematics, statistics, or quantitative disciplines. Who You Are: A natural problem-solver and independent More ❯

control, CI/CD pipelines, and test-driven development. Nice to Have: Experience within financial services or fintech. Familiarity with MLOps tools (e.g., MLflow, Kubeflow, SageMaker). Understanding of regulatory or compliance frameworks. Academic background in mathematics, statistics, or quantitative disciplines. Who You Are: A natural problem-solver and independent More ❯

control, CI/CD pipelines, and test-driven development. Nice to Have: Experience within financial services or fintech. Familiarity with MLOps tools (e.g., MLflow, Kubeflow, SageMaker). Understanding of regulatory or compliance frameworks. Academic background in mathematics, statistics, or quantitative disciplines. Who You Are: A natural problem-solver and independent More ❯

cross-functional teams. Preferred Qualifications PhD in Computer Science, AI/ML, or related field. Experience with production ML systems and MLOps pipelines using Kubeflow or Vertex AI Pipelines. Knowledge of transformers and large language models (LLMs). Understanding of recommender systems, natural language processing, or graph-based search engines. More ❯

or XGBoost Hands-on experience building and deploying ML models into production environments Familiarity with ML Ops workflows (e.g., MLflow, Airflow, Weights & Biases, or Kubeflow) Experience working with structured data (credit, payments, customer behaviour) and applying feature engineering at scale Understanding of model performance metrics, calibration, A/B testing More ❯

or XGBoost Hands-on experience building and deploying ML models into production environments Familiarity with ML Ops workflows (e.g., MLflow, Airflow, Weights & Biases, or Kubeflow) Experience working with structured data (credit, payments, customer behaviour) and applying feature engineering at scale Understanding of model performance metrics, calibration, A/B testing More ❯

or XGBoost Hands-on experience building and deploying ML models into production environments Familiarity with ML Ops workflows (e.g., MLflow, Airflow, Weights & Biases, or Kubeflow) Experience working with structured data (credit, payments, customer behaviour) and applying feature engineering at scale Understanding of model performance metrics, calibration, A/B testing More ❯

lifecycle tooling (deployment, monitoring and alerting) for our predictive models (for example claims cost, conversion, retention, market models) Maintain and improve the development environment (Kubeflow) used by our Data Scientists and Actuaries Develop and maintain pricing analytics tools that enable faster impact assessments, reducing manual work Collaborate with the technical More ❯

experiments through to production deployments, with tools such as Docker, Kubernetes & serverless alternatives such as AWS Lambda. Familiarity with MLOps tools such as MLFlow, Kubeflow or Sagemaker. A strong knowledge of cloud platforms (ideally AWS) and their respective services for deploying robust, AI-heavy applications. Bonus Experience: Experience with named More ❯

in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or email me at mmatysik@trg-uk.com. More ❯

in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or email me at mmatysik@trg-uk.com. More ❯

APIs Experience developing with containerisation (e.g Docker) and orchestration Kubernetes in cloud computing environments Familiarity with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo, etc.) Ability to translate business needs to technical requirements Strong understanding of software testing, benchmarking, and continuous integration Exposure to machine learning methodology More ❯

related position Proficient in Python, C++ Experience with distributed systems and parallel computing Familiarity with embedded systems development Experience with workload orchestration tools (Databricks, Kubeflow, Airflow, etc.) Familiarity with unstructured data processing (video, audio, ffmpeg) Experience working with model registries and model version control Strong understanding of REST API design More ❯

Python, experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g., Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI). #J-18808-Ljbffr More ❯

days per week (right to work in the UK required). Nice‐to‐haves Clinical or health‐tech domain knowledge. MLOps tooling (MLflow, Kubeflow, Vertex Pipelines). Benefits Competitive salary and attractive equity in a high growth startup 25 days holiday + UK bank holidays. Flexible hours & focus on sustainable More ❯

LakeFS , or Databricks . Knowledge of security and compliance best practices (e.g., SOC2, ISO 27001). Exposure to MLOps platforms or frameworks (e.g., MLflow, Kubeflow, Vertex AI). What We Offer Competitive salary + equity Flexible work environment and remote-friendly culture Opportunities to work on cutting-edge AI/ More ❯