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Drive the advancement of workload scheduling and orchestration across high-performance computing platforms, bridging HPC and AI environments. Lead technical initiatives and mentor engineers to ensure efficient and reliable compute workloads for researchers, data scientists, and engineers.

Tasks

  • Serve as the internal expert on the SLURM Workload Manager, architecting, scaling, and maintaining SLURM across heterogeneous HPC and AI environments to ensure high availability and dynamic resource distribution.
  • Design and tune advanced SLURM configurations, including custom plugin integration, topology-aware scheduling, GRES/GPU management, dynamic priority trees, and complex QoS/fair-share policies.
  • Evaluate and implement integrations between SLURM, Kubernetes, and orchestration platforms to streamline job submission workflows across architectures.
  • Integrate containerization standards across SLURM (using Singularity/Apptainer) while maintaining operational familiarity with Kubernetes container orchestration to support hybrid AI/HPC workloads.
  • Solve unique, unprecedented multi-tenant bottlenecks, such as GPU allocation overhead, MPI/NCCL communication failures, and complex workload failures.
  • Lead large, global cross-functional initiatives to establish workload orchestration standards, policies, and architectural patterns across Roche compute environments.
  • Act as a technical mentor and coach for junior and mid-level engineers, driving skill development and continuous learning.
  • Partner with Observability Engineers to establish deep telemetry dashboards for SLURM job efficiency, queue wait times, and hardware utilization, utilizing configuration-as-code to deploy policies uniformly.

Requirements

  • Bachelor’s or advanced degree in Computer Science, Applied Mathematics, Computational Engineering, or a related technical discipline.
  • Extensive systems engineering experience with deep specialization in workload scheduling, SLURM administration, and multi-tenant cluster optimization.
  • Demonstrated track record of leading complex technical initiatives and mentoring engineering peers.
  • Proven experience in life sciences, pharmaceutical R&D, or high-performance scientific research environments.
  • Subject matter expertise in architecting, scaling, upgrading, and optimizing production SLURM environments, including scheduler/backfill tuning, partition and topology design, priority/fair-share/QoS policies, cgroups, HA architecture, plugin integration, and GRES/TRES modeling for GPUs and specialized resources.
  • Deep expertise in SlurmDBD and accounting architecture, database performance and lifecycle management, scheduler telemetry and health monitoring, workload efficiency analysis, queue/wait-time diagnostics, utilization analysis, and troubleshooting complex controller, database, node, and workload interactions.
  • Hands-on experience with Kubernetes fundamentals and container runtimes (Singularity, Apptainer, Enroot, Docker) within an HPC context.
  • Deep familiarity with GPU scheduling (NVIDIA MIG, fractionalization), high-speed interconnects (InfiniBand, RoCE), and multi-node communication frameworks (MPI, NCCL).
  • Advanced proficiency with Infrastructure-as-Code (Ansible, Terraform) to automate scheduler deployments, configuration drift management, and telemetry pipelines.
  • Broad knowledge across HPC, AI infrastructure, Kubernetes, containers, networking/interconnects, observability, automation, and capacity management to solve orchestration problems spanning multiple technology domains.
  • Proven ability to troubleshoot complex, unprecedented failure modes at the intersection of hardware, OS, schedulers, and workloads.
  • Strong leadership presence with a dedication to mentoring colleagues, driving technical standards, and collaborating with global cross-functional teams.
  • Collaborative team player with demonstrated ability to coordinate initiatives across diverse global business units, IT functions, and scientific research stakeholders.
  • Passion for guiding the convergence of traditional HPC schedulers like SLURM with cloud-native, Kubernetes-driven AI workflows.

Benefits

At Roche, you are valued, accepted, and respected for who you are, allowing you to thrive both personally and professionally. The culture encourages personal expression, open dialogue, and genuine connections.

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Über uns
Roche ist ein international tätiges Schweizer Pharma- und Diagnostikunternehmen mit Sitz in Basel und entwickelt, produziert und vertreibt Medikamente sowie diagnostische Lösungen. Das Unternehmen ist in den Bereichen Pharma und Diagnostik tätig und fokussiert sich auf Forschung und Innovation in verschiedenen Therapiegebieten wie Onkologie, Neurologie und Infektionskrankheiten. Roche ist weltweit aktiv und zählt zu den führenden Unternehmen im Gesundheitsbereich.
Das Team

The Accelerated Compute Engineering (ACE) team acts as a center of excellence and delivery for High Performance Compute and AI Infrastructure across Roche, facilitating seamless onboarding and adoption for business vertical customers needing accelerated compute.

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