MSc Thesis: Cross-Lingual Safety & Identity with DPO

AI Sweden; Stockholms kommun; Hybrid; SEK 246,000 - 368,000; Full time

Benefits offered by this job

Hybrid/Remote options

Job summary

AI Sweden invites MSc students to join as thesis researchers focused on open-weight European AI models, identity consistency, and safety alignment across languages. You’ll design experiments, run evaluations, and contribute to a growing body of public research data.

Location is Hybrid (Gothenburg / Stockholm) or Remote. You will collaborate with leading AI scientists at AI Sweden, aiming for high-impact publications and practical demonstrations that advance Swedish industry and the public

Qualifications

• Pursuing MSc in Computer Science, Data Science, ML, or related field.
• Strong Python programming and practical experience with deep learning frameworks.
• Familiarity with LLM post-training alignment (SFT, DPO, RLHF) or context-extension.

Responsibilities

• Design experiments to assess identity consistency and safety across languages.
• Analyze and curate data, evaluate model behaviors, and compare training approaches.
• Implement and evaluate alignment strategies using open-weight models and multilingual datasets.

Skills

Python

PyTorch

Hugging Face

Distributed GPU

Education

Ongoing Master’s studies in Computer Science

Tools

Linux HPC

Job description

AI Sweden invites MSc students to join as thesis researchers focused on open-weight European AI models, identity consistency, and safety alignment across languages. You’ll design experiments, run evaluations, and contribute to a growing body of public research data.

Location is Hybrid (Gothenburg / Stockholm) or Remote. You will collaborate with leading AI scientists at AI Sweden, aiming for high-impact publications and practical demonstrations that advance Swedish industry and the public