Make intelligence open and accessible to all. Backed by Battery, Lightspeed and Sequoia.
About the role
The web is one of the most important sources of information for frontier AI systems. The quality, coverage, freshness, and diversity of web data directly influence model capabilities.
What they're looking for
- Experience building large-scale web crawling, search indexing, content acquisition, or internet-scale data collection systems
- Strong understanding of crawling architectures, URL frontier management, scheduling, and distributed crawl coordination
- Experience with large-scale distributed systems using technologies such as Ray, Spark, Beam, Flink, or similar frameworks
- Familiarity with content extraction, HTML parsing, browser automation, rendering systems, and modern web technologies
- Experience operating systems that process petabyte-scale datasets
- Strong systems engineering skills, including reliability, observability, performance optimization, and debugging
More about this role
Reflection is a research lab making intelligence open and accessible for everyone to use, customize, and build on. We build open models that let anyone control their intelligence and help shape the future of AI. Our mission: make intelligence open and accessible to all.
The web is one of the most important sources of information for frontier AI systems. The quality, coverage, freshness, and diversity of web data directly influence model capabilities.
As a member of the Data Team, your mission is to build and operate large-scale web crawling systems that continuously discover, acquire, and process content from across the internet. You will own the infrastructure that powers web-scale data collection, from URL discovery and scheduling to distributed crawling, content extraction, and dataset delivery.
You will work directly with world-class researchers to understand which parts of the web matter most for model performance and build systems that efficiently acquire high-value content at scale.
This role is ideal for engineers who love building distributed systems, optimizing large-scale crawlers, and solving the unique technical challenges of collecting data from the modern...
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