Head of AI Safety Research

Far Ai; Berkeley (CA); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Health Insurance

Retirement - 401(k) plan with up to 2%

PTO - 25 days Paid Time Off per year

Paid Bereavement, Family, Medical and

WFH Stipend & Equipment

Catered Meals (Berkeley Office Only)

Job summary

FAR.AI is hiring a Research Lead to develop and lead a research agenda that reduces catastrophic risks from advanced AI. You'll build and lead a team executing this agenda — mentoring Members of Technical Staff to scale your vision, and remaining hands-on enough to write code and run experiments yourself.

What counts is whether AI labs and governments actually change how they act; publications are useful but aren’t the measure.

Qualifications

• Strong research track record in AI safety.
• Ability to articulate a clear research agenda.
• Experience leading a team and mentoring junior researchers.
• Excellent communication for technical and non-technical audiences.

Responsibilities

• Articulate a research agenda with a theory of change for mitigating catastrophic risks from human-level or superhuman AI systems.
• Grow and lead a team of technical staff in pursuit of this agenda.
• Lead novel research projects with unclear markers of progress or success.
• Share research findings through publications and presentations to drive adoption and change.
• Mentor and coach junior team members in research skills and ML engineering.
• Contribute to FAR.AI's intellectual environment through feedback on proposals.
• Build a research field around your agenda through FAR.AI's grantmaking and events.

Skills

Team leadership

Mentoring

Research planning

Effective communication

Tools

Grant writing

Job description

FAR.AI is hiring a Research Lead to develop and lead a research agenda that reduces catastrophic risks from advanced AI. You'll build and lead a team executing this agenda — mentoring Members of Technical Staff to scale your vision, and remaining hands-on enough to write code and run experiments yourself.

What counts is whether AI labs and governments actually change how they act; publications are useful but aren’t the measure.