Technical Lead, AI Verification

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. Our current effort spans Singapore, USA, UK, Canada, and Germany, but we're looking to expand even further.

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 the 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, Intel, and RAND.

Just this summer, we plan to present our work at the AI Security Forum (Washington D.C.), ICML (Seoul), Australia AI Safety Forum (Sydney), and World AI Conference (Shanghai)

Your Work

This is a critical leadership role which tasked with making sure the best possible tools get built, building and managing a strong team, and interfacing with policymakers. Developing strong in-house capacity will be essential for steering this collaboration and whoever fills this role will be key to making this go well

Work spans the gamut — from developing algorithms for recomputing AI workloads, to ML engineering to set up inference pipelines, to frontend engineering of demos, to cybersecurity analysis of our designs. In all cases, you'd get to collaborate with external experts and the rest of our team.

• Our current project involves distinguishing between inference and training workloads on a GPU.
• Potential future projects: prototyping secure GPU enclosures, or designing privacy-preserving means of conducting white-box evaluations.

About You

Essentials

• Strong engineering or cybersecurity fundamentals.
• Familiar with key concepts in AI verification, cybersecurity, and/or confidential computing.
• Comfortable setting direction and spotting opportunities autonomously.
• Experience managing teams, coaching engineers, and setting specialisation.

Nice to Have

• Experience contributing to AI hardware engineering or confidential computing projects.
• Electrical engineering experience, particularly around network-level instrumentation.
• Ability to translate technical topics for a range of audiences.