About Neo Research

Neo Research (新衡) is an independent AI safety research organization based in Singapore. We study frontier risks in increasingly capable AI systems, with a particular focus on the open-weight model ecosystem and the rapidly growing frontier-model ecosystem in Asia.

Some of the world’s most capable open-weight models are now being developed in Asia and deployed globally. Yet, they remain poorly understood from a frontier-safety perspective. We want to understand how to ensure their safety, and what new risks become important as the frontier changes.

Our current work focuses on misalignment, loss of control, and harmful manipulation. We study questions such as whether models pursue unintended objectives, conceal problematic behaviour, recognize and adapt to evaluations, evade oversight, or become less safe as they are given greater autonomy. Our goal is to produce rigorous empirical evidence about risks that are important but difficult to measure.

We are looking for a Research Scientist to identify important questions and own research projects end-to-end, from initial hypothesis and experimental design through to analysis and publication.

Why join Neo Research

At Neo, you will have substantial freedom to pursue research questions you think matter. We are small enough that a strong researcher can materially change our agenda, while having the engineering support and external relationships needed to turn good ideas into serious empirical work.

You will work with research engineers, active projects, evaluation infrastructure, and growing external collaborations. You will have room to propose new directions, shape how we study difficult questions, and develop them into rigorous published work.

We are well positioned for research to reach the people making decisions about these models. We have presented our work to most major Chinese frontier-model developers and are running a joint evaluations project with an AI Safety Institute. We publish our results, but also work to put them directly in front of model developers, safety institutions, and policymakers who can act on them. Our mission statement describes the research questions we currently think are most important.

What you’ll do

• Own research projects end-to-end: identify important questions, formulate hypotheses, design experiments, analyse results, and publish the work.

• Develop rigorous evaluations of misalignment and loss-of-control risks, including evaluation awareness, sandbagging, dishonesty, sycophancy, and unsafe behaviour in agentic settings.

• Study behaviours that are difficult to observe directly, including long-horizon failure modes and cases where models may have incentives to conceal relevant behaviour.

• Investigate whether existing alignment and evaluation methods continue to work across different frontier-model ecosystems.

• Work closely with research engineers to turn research ideas into robust, reproducible experiments.

• Contribute to Neo’s broader research agenda and communicate findings to researchers, model developers, and safety institutions.

About you

Essentials:

• Track record of original research in AI safety, evaluations, or a closely adjacent field.

• Deep familiarity with frontier model behaviour and elicitation methodology.

• Ability to define a research agenda and drive it to concrete, published output.

• Strong technical writing.

• Comfortable collaborating closely with engineers.

• Comfortable in an ambiguous, early-stage research environment where the questions aren't settled yet.

Nice to have:

• PhD or equivalent research output.

• Publications on dangerous capability evaluations or alignment.

• Familiarity with frontier lab safety reports.

• Familiarity with the EU AI Act or NIST AI RMF.

• Reading and writing Mandarin.

You don't need to have worked in AI safety specifically. We're also interested in researchers from closely adjacent fields whose judgment and technical depth could transfer strongly to this work

Role logistics & benefits

Location:

This role can be based in Singapore or remotely.

Our team is globally distributed, so remote team members should be comfortable maintaining some working-hour overlap with colleagues across regions.

Compensation:

Our compensation takes location, experience, and level into account, with indicative salary ranges of $150,000 – $200,000+. We may offer above this range for exceptional candidates.

Benefits:

Competitive benefits and leave policies.