Research Engineer - AI Verification
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 57d ago
The date the source published, not the day we noticed it (2026-08-14). Last seen at its source 2h ago.
We have tracked this listing since 5 Oct 2026 (5 days). The employer's own board has carried it every time we have read it, most recently 2 hours ago.
Is it remote?
Remote/Flexible
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
Singapore, London, San Francisco
The description agrees: it names Singapore, United Kingdom.
What the ad says
…Location: This is a remote role that can be based in Singapore, the UK…
Pay not stated
Similar roles pay $177.5k–182.5k/yr
Middle 50% of 21 listings that do state pay — Engineering · all levels · Singapore · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Carried by 1 source
-
Ashby employer's own board first seen 5d ago · last seen 2h ago
The listing
About the team
The world is waking up to the fact that we will need ways to verify what's happening inside datacenters running large AI models — to enable international agreements, protect middle-power sovereignty, and facilitate trustworthy adoption of AI in high-stakes industries. But, for this to be trusted, it can't just be developed in a few countries.
Singapore AI Safety Hub is launching the first international collaboration aimed at changing that. Our Verification team builds prototypes of these tools in public to speed up the development and adoption of globally trusted verification mechanisms.
We're building tools that will translate into policy change in the real world because our team is doing more than just building. Our team is demonstrating these tools to policymakers globally, helping roadmap the path to production-scale verification mechanisms, and broadening the base of independent experts who can evaluate these tools.
Our partners include experts from the Future of Life Institute, University of Oxford, and more. Our core team has experience at Oxford, ByteDance, Centre for the Governance of AI, and Singapore Government. Our collaborators have worked with Arm and Intel.
Just this summer, we’ve presented our work at the AI Security Forum (Washington D.C.), ICML (Seoul), Australia AI Safety Forum (Sydney), and World AI Conference (Shanghai). Read more about the response here.
Why Join SASH
AI verification is still a young and highly talent-constrained field, while the need for credible mechanisms to support international coordination around advanced AI is becoming increasingly prominent, including in initiatives like Pacing the Frontier.
Joining SASH now means working on technical problems where the solution space is still open, with significant room to explore approaches, build prototypes, and influence what gets developed, what the team builds, and how this emerging field connects to real-world AI governance. Scenarios like AI 2040 illustrate the role technical verification mechanisms could eventually play in making international AI agreements credible in practice.
SASH is a young, fast-moving organization where finding opportunities and making things happen is the norm. You'll have substantial autonomy to build around promising ideas rather than inherit a mature roadmap, while working with an international network of technical experts and policymakers.
Your Work
As a Research Engineer, you'll help turn emerging ideas in AI verification into practical technical prototypes. We're seeing more interest in our prototypes than we currently have capacity to pursue, so additional engineering capacity will directly expand the mechanisms and approaches we're able to explore.
AI verification is still an open technical problem. Mechanisms need to be robust to attempts to evade them, privacy-preserving enough to be deployable, and auditable enough to earn the trust of governments and other stakeholders. Solving these problems can draw on ML engineering, cybersecurity, cryptography, hardware, and systems engineering.
Our current project involves distinguishing between inference and training workloads on GPUs. Future projects could include scaling zero-knowledge proofs of AI inference and developing privacy-preserving approaches to white-box evaluations.
In this role, you would:
Build prototypes supporting AI verification.
Support technical communications.
Collaborate with external experts.
Work across: ML engineering, inference pipelines, algorithms, frontend demos, and cybersecurity.
About You
Essentials
Strong ML engineering fundamentals.
Familiarity with AI verification, cybersecurity and/or confidential computing.
Comfortable in ambiguous early-stage environments.
Nice to Have
AI hardware engineering.
Confidential computing.
Cybersecurity instrumentation.
Startup experience.
Interest or experience working with Singaporean or Chinese stakeholders.
Role Logistics & Benefits
Location:
This is a remote role that can be based in Singapore, the UK, or remotely.
For candidates interested in relocating, SASH can provide visa sponsorship in the UK.
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. Salaries above the stated range may be available for exceptional candidates.
Benefits:
Competitive benefits and leave policies.