[Hiring] Research Engineer @Singapore AI Safety Hub

Role Description

We are looking for Research Engineers to build the experimental systems needed to evaluate increasingly capable models:

• Design, implement, and run evaluations of misalignment and loss-of-control risks in frontier models.
• Build realistic agent environments, scaffolds, and tool integrations for studying behaviour under increasing autonomy.
• Develop infrastructure for long-horizon experiments involving many model calls, actions, tools, and environment states.
• Own experimental reliability and reproducibility across model access, sampling, configuration, environment management, logging, and analysis.
• Work with research scientists to turn open-ended questions into tractable experiments, and identify cases where an apparent model behaviour is actually an artefact of the evaluation.
• Build tools for inspecting and analysing large collections of model trajectories and comparing behaviour across models and experimental conditions.
• Contribute experimental methodology, infrastructure, and technical analysis directly to published research.

Qualifications

• Strong Python and general software-engineering skills.
• Experience working with language models, agentic systems, or model evaluations.
• The ability to turn an underspecified research question into a reliable experimental setup.
• Strong engineering practices, particularly around reproducibility, testing, observability, and data integrity.
• The ability to investigate unexpected results across both the model and the surrounding infrastructure.
• Clear technical writing and communication skills.
• Comfort working in an early-stage environment where requirements and research directions evolve.

Requirements

• Experience with AI safety or dangerous-capability evaluations (helpful, but not required).
• Experience with evaluation frameworks such as Inspect (helpful, but not required).
• Experience building agent scaffolds or tool-use environments (helpful, but not required).
• Experience with distributed inference, large-scale API-based experimentation, Docker, Kubernetes, or related infrastructure (helpful, but not required).
• Experience analysing large collections of model trajectories or transcripts (helpful, but not required).
• Familiarity with frontier-model safety reports (helpful, but not required).
• Mandarin reading or writing ability (helpful, but not required).

Benefits

• Competitive benefits and leave policies.