3 jobs found in Munich

  These are the tasks you will be responsible for: Planning, building and operation of cloud-native platforms as well as deployment of microservices and containerized applications Development and optimization of CI/CD pipelines for the automated deployment of platform components Implementation of Infrastructure as Code and GitOps approaches (e.g., GitLab CI, Terraform, Crossplane, Ansible, ArgoCD) Conceptualization and execution of container builds (Docker, Buildah, Maven Jib) as well as management of artifacts (Nexus, Harbor) Monitoring, logging and alerting using Prometheus, Grafana, Instana Operation and optimization of highly available applications (PHP, Java, Node.js) Scaling and resource optimization in Kubernetes environments Implementation of application deployments via Helm charts, Kustomize or Kubernetes operators Model-based documentation of technical systems, CI/CD workflows, GitOps processes and service topologies...

Are you passionate about leading teams and delivering top-notch IT solutions for clients? As a leader with strong communication skills and a vision for a high-performance team, you will actively shape the future of our Atlassian and cloud projects as a Consulting Team Lead (m/f/d) at XALT. XALT Business Consulting GmbH is an Atlassian Platinum Solution Partner with 100% DevSecOps DNA and implements projects in areas such as ITSM, social intranets, cloud infrastructure, and identity management Team Leadership & Delivery: Professional and organizational management of the consulting team – planning the deployment of consultants in Atlassian and DevOps projects and ensuring timely, high-quality results as well as satisfied customers. Methodology & Processes: Definition and optimization of our consulting processes and best practices within the team, as well as the establishment of appropriate methods and continuous improvements. Customer escalations: Direct...

Your mission Design and maintain scalable pipelines to ingest and organize large volumes of time-series camera and sensor data (RGB, IR, acoustic, depth, IMU, and other modalities). Own and improve datasets for object detection and classification tasks, ensuring statistical robustness, diversity, and representativeness. Build and operate active learning loops to select high-value samples, reduce annotation cost, and continuously improve model performance. Write robust preprocessing pipelines using Python, NumPy, Pandas, and augmentation libraries like Albumentations. Manage labeling workflows, including QA rules, label consistency checks, vendor coordination, and dataset versioning. Collaborate with ML Engineers to fine-tune, train, and evaluate object detection models and feed insights back into the data pipeline. Analyze model weaknesses, uncover blind spots, and drive dataset improvements through statistical diagnostics and drift/bias detection. Create...