[Hiring] Verification Lead @Singapore AI Safety Hub

Role Description

This is a critical leadership role with substantial scope to define the technical direction of SASH's Verification program. You'll help decide which technical bets are most important to pursue, turn promising ideas into practical prototypes, and build the team and capabilities needed to advance them.

• Set technical direction:
  • Identify promising verification problems and approaches.
  • Decide which bets are worth pursuing.
  • Steer projects from idea through prototype.
• Build and prototype:
  • Work across problems such as algorithms for recomputing AI workloads.
  • ML engineering for inference pipelines.
  • Frontend engineering for demonstrations.
  • Cybersecurity analysis of verification designs.
• Build the team:
  • Manage and coach engineers.
  • Help set areas of specialization.
  • Grow SASH's in-house verification capabilities.
• Collaborate with technical experts:
  • Work with external experts and SASH's broader team across cybersecurity, ML, hardware, cryptography, confidential computing, and adjacent fields.
• Interface with policymakers:
  • Help translate technical work and trade-offs for policymakers and other stakeholders.
  • Ensure the mechanisms we're developing respond to real-world verification needs.

Qualifications

• Strong engineering, systems, cybersecurity, or adjacent technical fundamentals.
• Expertise relevant to AI verification, such as cybersecurity, confidential computing, AI infrastructure, hardware, cryptography, or related systems domains.
• Comfortable operating in an ambiguous technical environment: identifying promising directions, setting priorities, and moving from ideas to prototypes.
• Experience leading technical work and developing others, including managing or coaching engineers.
• Strong communication skills, including the ability to explain technical problems and trade-offs to different audiences.

Requirements

• Experience with AI hardware, datacenter infrastructure, or confidential computing.
• Electrical engineering experience, particularly around network-level instrumentation.
• Experience with cryptographic or privacy-preserving systems.
• Experience translating research or technical prototypes into real-world applications.
• Familiarity with AI safety, AI governance, or technical verification.

Benefits

• Competitive benefits and leave policies.