Safety Operations Lead

Thinking Machines Lab•San Francisco, CA

7d•$190,000 - $300,000•Onsite

About The Position

We’re looking for a Safety Operations Lead who will focus on making our products safe by default while supporting fast product iteration and ambitious ideas. You’ll work closely with product engineers, security, researchers, and designers to bake safety and integrity into the way we design, build, and ship human-AI collaboration tools. Day to day, you'll be in the moderation queue while building the tooling and policy that make the next round of moderation faster and more accurate.

Requirements

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 specific policies or enforcement programs you've built or run.
Direct case experience with at least one of: cybersecurity abuse, CBRN-relevant risk, youth safety, or prompt injection, in a production environment.
Working familiarity with model safety and abuse risk categories (jailbreaks, prompt injection, scaled abuse) and how to identify and mitigate them in a live product, evidenced by specific cases you've handled.
Practical experience using AI tools (Claude, Codex, or similar) to build or accelerate operational workflows, not just as a general user of these tools.

Nice To Haves

Experience with safety and integrity operations specifically on AI-powered products or LLM APIs, and their unique abuse patterns.
Track record of turning recurring case patterns into reusable tooling, workflows, or process improvements, while still owning the underlying queue rather than handing it off once the interesting part is solved.
Experience training, onboarding, or setting the quality bar for other moderators or reviewers, showing you scale a team's output rather than just your own.

Responsibilities

Review flagged content, safety escalations, and account-level abuse signals daily. This is a standing responsibility, not a rotation: you'll triage cases, apply policy judgment, and take action (content flags, account review, bans/recovery) on an ongoing basis.
Use patterns from that casework to design and refine safety policy across the product stack, working with engineering, legal, safety research, and security stakeholders.
Build and maintain tooling and automation that make your own casework faster and more consistent: triage agents, ban/recovery workflows, abuse detection frameworks and templates.
Partner with product teams to embed safety into the product experience: model refusals, content flagging, account review, and safety protections, informed by what you're seeing in the queue.
Improve observability and detection for safety-relevant events (model safety trends, abuse patterns, malicious behavior in production), so the next round of cases surfaces faster and with better signal.