Teams at Thinking Machines Lab

Build and own internet-scale web-crawling and ingestion systems for pretraining data. Responsibilities include designing distributed crawlers, extraction and deduplication pipelines, data-quality filtering, specialized crawlers, and petabyte-scale infrastructure. The role partners with pretraining teams to assess model impact, improves system reliability and efficiency, and helps define technical direction. Candidates need extensive experience with web crawlers or large-scale data acquisition, distributed systems, and the practical and legal aspects of web data collection.

Design, build, and operate secure sandboxing infrastructure for untrusted, model-generated code and tool calls. Responsibilities include improving isolation with containers and microVMs, developing scheduling and resource-management systems, scaling concurrent executions, adding observability and abuse detection, and owning platform reliability and performance. The role partners with researchers and product teams to provide safe, usable sandboxing primitives.

Lead and build Thinking Machines’ product policy function, establishing usage, content, safety, model release, and developer-facing policies. Hire and manage a team, create product and model risk review frameworks, develop decision-making infrastructure, and partner with Research, Product, Trust & Safety, Communications, Public Policy, and Legal. Translate complex AI policy questions into actionable executive recommendations and responsible launch mitigations.