LLM Post-Training Engineer | HPC & RL Pipelines

ETH Zürich; Zürich; Hybrid; CHF 110.000 - 170.000; Vollzeit

Benefits dieser Stelle

Access to HPC infrastructure

Open-source collaboration

Zusammenfassung

ETH Zürich seeks an engineer to join Apertus post-training efforts, developing, running, and evaluating SFT and RL pipelines to turn base models into capable assistants. The role emphasizes collaboration in an HPC research environment.

You will work across LLM post-training, containerised environments, Slurm jobs on Alps/CSCS, and close coordination with researchers from EPFL and ETH Zürich, contributing to open, multilingual AI models and scalable experiments.

Qualifikationen

• Experience in AI and neural network architectures.
• Hands-on experience with LLM post-training (SFT, preference optimisation) or reinforcement learning.
• Strong collaboration and communication across research and engineering teams.
• Project or study-based experience; formal work experience preferred.
• Flexibility with shifting priorities and schedules.
• Ability to work in an HPC environment with researchers and CSCS engineers.

Aufgaben

• Develop, run, and evaluate scalable post-training workflows for Apertus.
• Build and maintain containerised environments for LLM post-training and RL workloads.
• Adapt containers for execution on Alps/CSCS infrastructure.
• Run Slurm-based training and evaluation jobs.
• Debug distributed execution, checkpointing, filesystem performance, networking, and GPU utilisation.
• Collaborate with researchers and CSCS engineers to improve reliability and performance of large-scale experiments.
• Support SFT, preference optimisation, and reinforcement learning workflows.
• Build RL environments for tasks with verifiable outcomes.
• Run ablation studies and evaluate model behaviour across benchmarks.

Kenntnisse

LLM post-training experience

HPC collaboration

Research collaboration

Distributed training

Software engineering

Ausbildung

MSc or PhD in Computer Science / AI / ML

Exceptional BSc candidates with strong engineering background

Tools

Slurm

Docker / containerization

Megatron-LM / DeepSpeed

veRL / TRL / vLLM

Jobbeschreibung

ETH Zürich seeks an engineer to join Apertus post-training efforts, developing, running, and evaluating SFT and RL pipelines to turn base models into capable assistants. The role emphasizes collaboration in an HPC research environment.

You will work across LLM post-training, containerised environments, Slurm jobs on Alps/CSCS, and close coordination with researchers from EPFL and ETH Zürich, contributing to open, multilingual AI models and scalable experiments.