Research Crawling Engineer

As a Research Crawling Engineer, you will design and operate large-scale web data acquisition systems for research and model development. You will work will span distributed systems, scraping infrastructure, and data pipelines. Responsibilities:

Build and maintain large-scale web crawlers across diverse domains

Design high-throughput, fault-tolerant systems for data collection (millions to billions of URLs/day)

Handle anti-bot systems, rate limits, and dynamic/JS-heavy sites

Develop pipelines for cleaning, deduplication, filtering, and normalization

Construct and maintain datasets for research and model training

Monitor crawl performance, coverage, and data quality; iterate quickly

Collaborate with research teams to align data collection with modeling needs

Optimize infrastructure for cost, latency, and reliability

Requirements:

Strong programming experience in one or more of: Go, Rust, Python, Java, or C++

Experience building web crawlers or large-scale data pipelines

Solid understanding of HTTP, networking, and browser behavior

Familiarity with distributed systems and parallel processing

Experience working with large datasets (TB–PB scale preferred)

Ability to debug unstable or adversarial environments

Experience with NLP pipelines or dataset curation for ML

Familiarity with LLM pretraining data or retrieval systems

Experience with headless browsers (e.g., Chrome DevTools Protocol, Playwright, Puppeteer)

Knowledge of proxy systems, IP rotation, and large-scale request orchestration

Background in data quality evaluation or benchmarking

Experience running workloads on cloud or bare-metal infrastructure

Operating at the boundary of scale and reliability

Adapting to constantly changing web environments

Balancing throughput, coverage, and data quality

Owning end-to-end data acquisition pipelines

Ability to design systems that scale without degrading quality

Practical problem-solving under real-world constraints

Speed of iteration and ownership

Measurable improvements in data coverage, quality, or efficiency

Opportunity. We are at the forefront of developing a web-scale crawler and knowledge graph that improves access to public web data and extends the value of AI to the people.

Culture. We're a lean team with a high bar. We come to work not to be comfortable, but to find out what we're capable of and to do work that matters. We're not calling for people who keep things moving. We're calling for people who make everyone around them better. We prioritize low ego and high output. This is a fully remote team.

Compensation. You’ll receive a competitive salary, benefits and equity package.