Remote HPC LLM Post-Training & RL Engineer

Eidgenössische Technische Hochschule Zürich; Zürich; Hybrid; CHF 120.000 - 170.000; Vollzeit

Benefits dieser Stelle

Remote work options

Access to HPC infrastructure

Zusammenfassung

ETH Zürich is seeking a skilled engineer to join the Apertus post-training effort. You will develop, run, and evaluate SFT and reinforcement learning pipelines to turn Apertus base models into capable assistants, in a research-focused HPC setting.

You will work with researchers and engineers across ETH Zürich, EPFL, and CSCS, building containerised environments and running Slurm-based jobs on Alps infrastructure. Flexible remote work options are available.

Qualifikationen

• MSc or PhD in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or related field
• Exceptional BSc candidates with strong engineering experience will also be considered
• Experience in AI and neural network architectures
• Strong collaboration and communication skills and ability to work across research and engineering teams
• Prior hands-on experience in the core domains of this role is required
• This can be project or study based experience; formal work experience is preferred
• A high degree of flexibility: priorities, tools, and day-to-day tasks shift with training schedules, releases, and a fast-moving field
• Hands-on experience with LLM post-training, be it alignment (SFT, preference optimisation) or reinforcement learning
• Experience with frameworks such as veRL, slime, Megatron-LM, DeepSpeed, TRL, vLLM, SGLang, or similar tools

Aufgaben

• Build and maintain scalable post-training workflows for Apertus
• Run and monitor distributed training jobs on HPC infrastructure
• Debug failures in distributed execution, checkpointing, and GPU utilisation
• Collaborate with researchers and CSCS engineers to improve reliability of large-scale experiments
• Support SFT, preference optimisation, and reinforcement learning workflows
• Develop RL environments and verifier-based training

Kenntnisse

LLM post-training

HPC collaboration

Distributed training

Slurm HPC

Containerization

Research collaboration

Ausbildung

MSc or PhD in CS/DS/AI/ML

Strong engineering experience (BSc)

Tools

veRL

slime

Megatron-LM

DeepSpeed

TRL

vLLM

SGLang

Jobbeschreibung

ETH Zürich is seeking a skilled engineer to join the Apertus post-training effort. You will develop, run, and evaluate SFT and reinforcement learning pipelines to turn Apertus base models into capable assistants, in a research-focused HPC setting.

You will work with researchers and engineers across ETH Zürich, EPFL, and CSCS, building containerised environments and running Slurm-based jobs on Alps infrastructure. Flexible remote work options are available.