HPC Systems Engineer – Machine Learning Infrastructure & Operations (Informatiker/in)

ML CloudThe Cluster of Excellence "Machine Learning - New Perspectives for Science" at the Universityof Tübingen offers a position asHPC Systems Engineer – Machine Learning Infrastructure & Operations(m/f/d, E13 TV-L, 100%)The position is available in the team of the Machine Learning Science Cloud and is permanent.About UsThe ML Cloud team designs, runs and safeguards high-performance computing infrastructuretailored to machine learning workloads. Our state of the art systems are distributed across fourdata centers and are operated for the Tübingen AI Center, the Cluster of Excellence ’MachineLearning: New Perspectives for Science’ and the Hertie Institute for AI in Brain Health. Everyday, researchers unleash thousands of compute jobs on our systems, training frontier-scaleneural networks and running experiments.The OpportunityOur clusters keep growing – more GPUs, more storage, and more services around them. Weare looking for an HPC Systems Eingineer who enjoys developing and running productioninfrastructure end to end: from bare-metal compute and the Slurm scheduler to the virtualizationlayer on which central service run, the storage backends and the automation that holds it alltogether. You will keep our systems fast and reliable, extend them as demand grows, and turnmanual work into reproducible, code-driven operations that the whole team can rely on. Youwill be joining a motivated team of HPC specialists who share responsibility for the wholestack, work closely, and have real room to shape how our infrastructure is built and run. Youwill also have the opportunity to shape two new directions: AI agents in our administrativeworkflows, and agent-native access to the clusters for our users.Your Tasks• Design and operate HPC clusters across four data centers – spanning inter-/intra-sitenetworks, SLURM scheduling, parallel filesystems (e.g., Lustre/Ceph), and GPUaccelerators – ensuring high availability and sustained throughput for researchworkloads.• Build and manage provisioning and configuration of heterogeneous compute, storageand network nodes (e.g. image-based provisioning, node lifecycle, Layer 2 and Layer 3networking)ML Cloud• Run and extend our Proxmox virtualization clusters hosting the management plane andinfrastructure services (HA, live migration, backup)• Operate and scale our storage platforms: Ceph clusters for S3-compatible object storagefor research data, including capacity planning, tiering, replication and backup• Automate operations as code with Ansible and Git-based workflows – provisioning,configuration, roll-outs and recurring maintenance• Build and operate monitoring, logging and alerting, and keep systems patched, hardenedand reliable through regular maintenance windows• Plan and carry out hardware roll-outs, capacity extensions and migrations together withvendors and data center staff• Bring AI agents into our admin workflows and build agent-native access to the clusterfor users.• Support and advise users on efficient cluster usage (job scheduling, data handling,storage layout, access workflows)Your Profile• Masters degree in Computer Science or a related field• Solid Linux administration experience in a production environment(RHEL/Rocky/Ubuntu)• Hands-on HPC experience: Slurm, parallel file systems (Weka, Lustre, Ceph), GPUworkloads (driver/CUDA, DCGM, Fabric Manager, NVLink/NVSwitch, MIG) andhigh-speed networks (InfiniBand, 400G Ethernet)• Solid data-center networking skills: Ethernet/IP (VLANs, routing, bonding/LACP),InfiniBand fabric management (subnet manager, fabric diagnostics), and firewall/VPNconfiguration• Experience operating Ceph and S3-compatible object storage (e.g. RADOS Gateway)at scale• Experience with virtualization for the management plane and infrastructure services(Proxmox, including clustering and backup)• Strong automation skills with Ansible (roles, inventories, CI-driven roll-outs) andscripting in Bash and Python• containers (Apptainer/Singularity/Docker), monitoring stacks (Prometheus/Grafana), ordatabase and service operations• A plus: Hands-on LLM tooling (tool calling and APIs, agent frameworks, retrieval andevaluation)• Independent, structured working style and good communication in English; German isa plus• A collaborative, user-facing mindset – comfortable supporting and advising researchersML CloudWhat We Offer• Technically deep, architecturally open work that directly enables cutting-edge machinelearningresearch• A small, senior team with flat hierarchy• Flexible working hours and the option to work partially from home• Working in an English-speaking, international team of HPC experts• Professional development, conference attendance and real influence on our roadmapInterested? We'd love to hear from you!Disabled candidates will be given preference over other equally qualified applicants. TheUniversity of Tübingen is committed to equal opportunities and diversity and actively promotesgender equality. The position is divisible.Please submit your application, including CV and relevant transcripts by December 6, 2026 viaour application portal careers.tuebingen.ai. For questions, please contact Simon Kreuzer at[email protected]. The position is available from now on. Hiring is done by theCentral Administration of the University of Tübingen.Ergänzende Informationen:Anforderungen an den Bewerber: Grundkenntnisse: Machine Learning