Operations Analyst, Safety

Thinking Machines Lab•San Francisco, CA

3h•$190,000 - $300,000•Onsite

About The Position

Thinking Machines Lab is seeking an Operations Analyst to focus on ensuring product safety while supporting rapid product development. This role involves close collaboration with product engineers, security, researchers, and designers to integrate safety and integrity into the AI development lifecycle. The day-to-day responsibilities include managing a moderation queue and developing the tools and policies to improve efficiency and accuracy in future moderation efforts.

Requirements

2+ 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 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 handled.
Practical experience using AI tools (Claude, Codex, or similar) to build or accelerate operational workflows, not just as a general user.

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.
Experience training, onboarding, or setting the quality bar for other moderators or reviewers.

Responsibilities

Review flagged content, safety escalations, and account-level abuse signals daily, including triaging cases, applying policy judgment, and taking action on content flags, account reviews, bans, or recoveries.
Design and refine safety policies across the product stack based on casework patterns, collaborating with engineering, legal, safety research, and security teams.
Build and maintain tooling and automation to enhance the speed and consistency of casework, such as triage agents, ban/recovery workflows, and abuse detection frameworks.
Partner with product teams to integrate safety into the user experience, including model refusals, content flagging, account review, and safety protections.
Improve the detection and observability of safety-related events, such as model safety trends, abuse patterns, and malicious production behavior, to expedite case surfacing and improve signal quality.