10 of 10 Kubeflow Jobs in the South East

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 ❯

and training across GPUs and cloud-based architectures. Ensure security and compliance for ML platforms handling sensitive data. Evaluate and integrate MLOps tools (MLflow, Kubeflow, etc.) to enhance efficiency. Implement monitoring and alerting systems to detect anomalies and maintain model reliability. What We’re Looking For 3+ years of experience 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 ❯

to manage cloud infrastructure to ensure high availability, scalability, and cost efficiency. Nice-to-Have · Experience with ML orchestration platforms like MLflow, SageMaker Pipelines, Kubeflow, or similar. · Familiarity with model quantization, pruning, or other performance optimization techniques. · Exposure to distributed training frameworks like Unsloth, DeepSpeed, Accelerate, or FSDP. More ❯

SOC 2). Collaborate with ML/AI Teams Package and deploy large‑language‑model (LLM) training jobs on distributed GPU clusters (Slurm, Ray, Kubeflow, or AWS SageMaker). Optimize model‑serving (Triton, vLLM, TorchServe) for low‑latency, high‑throughput inference. Cost & Performance Optimization Track cloud spend, right‑size resources More ❯

Kernel, and tools such as MS tooling, Co-Pilot Studio, ML Studio, Prompt flow, Kedro, etc. Proficiency with pipeline orchestration tools, such as Airflow, Kubeflow, and Argo. Outstanding communication skills, combining subject matter expertise with a flair for statistics. A results-driven attitude, a passion for innovation, and a self More ❯

programming proficiency in Python, with additional experience in C/C++ for performance-sensitive applications. • Tooling Knowledge: Proficiency in MLOps frameworks such as MLflow, Kubeflow, or SageMaker Pipelines; familiarity with Docker and Kubernetes. • Optimization Techniques: Hands-on experience with model performance optimization techniques and distributed training frameworks (e.g., DeepSpeed, FSDP More ❯

Tadaweb is a pioneering technology company with roots in Luxembourg and a growing global presence, with offices in the United Kingdom, France, and the United States. For over 13 years, we’ve been on a mission to make the world More ❯

unstructured data. Implemented ML platform in enterprise client experience of ML use-cases AIML Platforms: DataRobot, Dataiku, Anaconda, Sagemaker, Vertex etc. AIML Frameworks: MLFlow, KubeFlow, BentoML, TensorFlow etc. AIML Development: PyTorch, Jupyter Notebooks, XGBoost, Tensorflow etc. AIML Models: Linear/Logistic Regression, KNN, Decision Trees, Anomaly Detection, LLMs, Generative Models More ❯

data pipelines across cloud/on-premises, using Azure and other technologies. Experienced in orchestrating data workflows and Kubernetes clusters on AKS using Airflow, Kubeflow, Argo, Dagster or similar. Skilled with data ingestion tools like Airbyte, Fivetran, etc. for diverse data sources. Expert in large-scale data processing with Spark … or Java, cloud SDKs and APIs. AI/ML expertise for pipeline efficiency, familiar with TensorFlow, PyTorch, AutoML, Python/R, and MLOps (MLflow, Kubeflow). Solid in DevOps, CI/CD automation with Bitbucket Pipelines, Azure DevOps, GitHub. Automate deployment of data pipelines and applications using Bash, PowerShell, or More ❯