AI Safety & Moderation Operations Lead

Thinking Machines Lab Inc.; San Francisco (CA); On-site; USD 190,000 - 300,000; Full time

Benefits offered by this job

Health, dental & vision benefits

Unlimited PTO

Paid parental leave

Relocation support

Job summary

Thinking Machines Lab is seeking a Safety Operations Lead to fortify safety by default while enabling rapid product iteration in human-AI collaboration tools. You’ll triage cases, define policy, and build tooling with cross-functional partners to scale safe adoption.

Based in San Francisco, you’ll influence model safety, abuse detection, and account reviews, driving measurable improvements in queue throughput and risk mitigation across the product stack.

Qualifications

• 7+ years in an operational trust & safety, content moderation, or fraud/abuse ops role with direct, recurring responsibility for a case queue.
• Experience owning policy definition, operationalization, and enforcement end to end, evidenced by policies or programs you've built.
• Direct case experience with cybersecurity abuse, CBRN-relevant risk, youth safety, or prompt injection in production.

Responsibilities

• Review flagged content, safety escalations, and account abuse signals daily. triage cases, apply policy judgment, and take action (flags, reviews, bans) continuously.
• Design and refine safety policy across the product stack with engineering, legal, safety research, and security stakeholders.
• Build and maintain tooling and automation to speed up casework (triage workflows, ban/recovery, abuse detection templates).
• Partner with product teams to embed safety into the product experience (model refusals, flagging, account review).
• Improve observability and detection for safety-relevant events to surface faster with better signal.

Skills

Trust & safety operations

Policy enforcement

Case management

AI safety familiarity

Tooling & automation

Job description

Thinking Machines Lab is seeking a Safety Operations Lead to fortify safety by default while enabling rapid product iteration in human-AI collaboration tools. You’ll triage cases, define policy, and build tooling with cross-functional partners to scale safe adoption.

Based in San Francisco, you’ll influence model safety, abuse detection, and account reviews, driving measurable improvements in queue throughput and risk mitigation across the product stack.