Safety Operations Lead
Thinking Machines Lab is hiring a Safety Operations Lead for a remote role open to applicants in United States. It pays $250k-$300k a year and Level rates it ; you can apply on Thinking Machines Lab.
Level's read on this job
- Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting lists this role as remote.
- Thinking Machines Lab mentions visa sponsorship in this posting.
- Tools and skills the posting cites include Claude, Codex and trust and safety.
- Level lists 57 other open roles at Thinking Machines Lab.
AI in this role
Manage trust and safety operations, content moderation, and safety policy enforcement for human-AI collaboration tools.
The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building is human, and we're hiring people who want to build it.
About the Role
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.
What You’ll Do
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.
Skills and Qualifications
Minimum 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 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.
Preferred qualifications:
We encourage you to apply even if you don’t meet all preferred qualifications.
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.
You’ll Thrive in This Role if
You have thoughtful opinions about what safe, trustworthy, frictionless user experiences look like, and you test those opinions against real cases in the queue, not just in the abstract.
You can translate safety and technical constraints into clear product trade-offs and feature requirements, but you see that as something that grows out of daily casework, not a substitute for it.
You bias toward speed and learning, and you measure that bias by how much faster or better the queue runs this month, not by how many new risk categories you've personally discovered.
Logistics
Location: This role is based in San Francisco, California.
Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $250,000 - $300,000.
Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.
As set forth in Thinking Machines' Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
How we rate this
Safety Operations Lead at Thinking Machines Lab rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where trust and safety was part of your work. What did you do?
- Tell me about a project where content moderation was part of your work. What did you do?
- Tell me about a project where policy definition was part of your work. What did you do?
- Tell me about a project where fraud detection was part of your work. What did you do?
- Tell me about a project where safety operations was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Trust And Safety, Content Moderation, Policy Definition, Fraud Detection, and Safety Operations. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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