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About Sybilion Sybilion builds AI-driven market forecasting for process industries (chemicals, packaging, pulp & paper, textiles, and broader manufacturing). We help procurement, supply chain, and commercial teams make better buy/sell decisions by turning messy external signals and internal operational data into clear, defensible forecasts that teams trust and act on. Our stack includes Python-based microservices, Postgre SQL data infrastructure, and ML/AI workflows that support forecasting models and decision tooling. About the Role We’re hiring someone to own both our platform and data infrastructure: Kubernetes administration, Linux systems, CI/CD, observability, and Postgre SQL administration for our data lakes and ML pipelines. You’ll keep production reliable, fast, secure, and scalable, while supporting the day-to-day needs of our engineers and ML workflows. This is an on-site role in Maia (Porto). We value in-person collaboration and move quickly. What You’ll Do Platform / Kubernetes / Systems Design, deploy, and operate Kubernetes clusters in production (networking, storage, security) Operate Linux server infrastructure (Ubuntu/RHEL), patching, hardening, and reliability Manage Docker image lifecycle (builds, optimisation, registry management, security scanning) Implement and maintain CI/CD pipelines for microservices deployments and infrastructure changes Build and maintain Infrastructure as Code (Terraform, Ansible, Helm) and Git workflows Operate and improve monitoring, logging, and alerting (Prometheus/Grafana, ELK/EFK/Loki, etc.) Manage secrets and credentials securely (Vault, Sealed Secrets, or equivalent) Ensure high availability, capacity planning, incident response, and disaster recovery readiness Support GPU-enabled workloads and ML/LLM deployments (resource allocation, utilisation, scaling) Postgre SQL / Data Infrastructure Administer and optimise Postgre SQL databases and data lake infrastructure (performance, reliability, cost) Own backup/recovery and disaster recovery procedures (including point-in-time recovery) Design schemas, indexing strategies, and query optimisation approaches; analyse execution plans Manage migrations and versioning (schema changes, rollout strategies, rollback plans) Implement replication/failover/clustering patterns for high availability Own database security: access controls, encryption at rest/in transit, audit logging, compliance needs Python Microservices / Data Pipelines / ML Workflows Support deployment and troubleshooting of Python microservices (Fast API/Flask/Django or similar) Help maintain Python environments and dependency management (pip/poetry/conda/mamba) Support ETL/ELT pipelines feeding our data lake and ML training workflows Implement data quality checks and validation where needed Partner with engineers and ML team to improve runtime performance, reliability, and operational visibility Must-Have Experience (Required) 5+ years of hands-on production experience in: Linux, Docker, Kubernetes, and Postgre SQL Strong Kubernetes administration skills (clusters, networking, ingress, storage, RBAC, security) Strong Postgre SQL administration skills (performance tuning, backups, replication/HA, security) Strong Linux systems skills (operations, troubleshooting, hardening) CI/CD experience (Git Hub Actions/Git Lab CI/Jenkins or similar) Infrastructure as Code experience (Terraform and/or Ansible; Helm for Kubernetes) Observability experience (metrics, logs, alerting; root-cause analysis) Solid Python literacy for debugging services and automating operational tasks Strong communication skills in English and comfort working independently end-to-end Willingness to participate in an on-call rotation for critical systems Preferred (Nice to Have) Startup background (you’ve worked in small teams, moved fast, and owned outcomes end-to-end) Experience running ML infrastructure (MLflow, Kubeflow, Airflow, KServe/Torch Serve, etc.) GPU cluster experience (NVIDIA GPU Operator or similar) and model serving optimisation Experience with service mesh (Istio/Linkerd) Experience with cloud managed databases (AWS RDS, GCP Cloud SQL, Azure Database) Familiarity with data lake / warehouse patterns and data versioning (DVC/MLflow tracking) Experience with Redis/Mongo DB or other complementary data systems Soft Skills We Value Strong problem-solving and analytical mindset Calm, structured incident handling and good judgement under pressure Proactive improvement orientation (you spot issues before they become outages) High bar for security, documentation, and operational hygiene Collaborative approach with product, engineering, and ML teams What We Offer €40,000–€70,000 salary range (depending on experience) Professional development and training budget Modern office environment in Maia, Porto Opportunity to work with cutting-edge ML/AI infrastructure and real-world data systems Career growth path within a growing technology organisation Coffee and snacks Work Environment This is an on-site position based in our Maia office. We value in-person collaboration and believe being together improves speed, clarity, and ownership.