Apertus Engineer: Infrastructure

Position

Vollzeit

Befristet

Mid

Ingenieurwesen

Konditionen

Lausanne, Waadt

100%

Anforderungen

Master

EU/EFTA-Bewilligung

Skills

CollaborationSystemic improvementsCUDANCCLPyTorchLinuxVersion controlDocumentationCI/CDModel servingDependency ManagementContainerization technologies

Sprachen

Englisch

Beschreibung

The engineer will enable stability and throughput for the Apertus pre-training and post-training pipelines by maintaining the ML system images and partnering with CSCS on the underlying infrastructure.

Aufgaben

Build, maintain, and upgrade container images for all core ML development phases: pre-training, post-training/alignment, and model serving/deployment
Target the ARM-based (aarch64, Grace-Hopper) node architecture of Alps, managing the full dependency stack (CUDA, NCCL, PyTorch, training and serving frameworks)
Keep image builds reproducible, versioned, and documented, including CI for builds and upgrades
Validate images against reference pre-training and post-training workloads together with Apertus engineers, and maintain working launch examples
Serve as the primary technical point of contact with CSCS engineers and researchers regarding compute, reliability, and efficiency
Work collaboratively with CSCS staff to identify and implement improvements in the efficiency and performance of the underlying compute infrastructure
Contribute to systemic improvements in CSCS-based resources (network, storage, scheduling) relevant to large-scale LLM training
Document and disseminate institutional knowledge about the CSCS infrastructure and best practices for leveraging these high-performance systems
Stress test the infrastructure using representative pre-training and post-training workloads
Work closely with Apertus pre-training and post-training engineers to debug cluster-level problems affecting stability and throughput
Support the Apertus serving stack, which builds on the same images

Anforderungen

MSc or PhD in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field
Exceptional BSc candidates with strong engineering experience will also be considered
Hands-on experience with HPC environments: job schedulers such as Slurm, shared filesystems, and multi-node GPU systems
Strong Linux systems and container skills (Docker/Podman and HPC runtimes such as enroot or Apptainer)
Strong collaboration and communication skills and ability to work across research, engineering, and operations teams
Prior hands-on experience in the core domains of this role is required
A high degree of flexibility: priorities, tools, and day-to-day tasks shift with training schedules, releases, and a fast-moving field

Technologien

DockerPodmanCUDANCCLPyTorch

Vorteile

A stimulating academic environment at one of the world's leading technical universities
Access to Alps, one of the largest AI-ready supercomputers in Europe
The opportunity to work alongside and intersect with leading researchers in the field
Collaboration with top researchers and engineers from EPFL, ETH Zürich, CSCS, and other Swiss institutions
Attractive employment conditions and comprehensive benefits, including the ETH Zürich/EPFL pension plans
Flexible working arrangements, including options for remote work
Professional development opportunities, including conference attendance and specialised training
The chance to contribute to open-source projects with global impact
Being part of Switzerland's sovereign AI development, working on technology with national significance

Unternehmen

ETH Zurich

Education

ETH Zurich is one of the world-s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct tra

Kontakt

Dr. Imanol Schlag

ischlag@ethz.ch