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Open nowPosted 169 days ago

Research Crawling Engineer

Startup Talents179 open roles

Where
London, New York, United States
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Your applicationOpen nowResearch Crawling EngineerStartup Talents · London, New York, United States

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Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 169 days ago

The posting

The employer is a decentralized, Solana-based web-scraping network that allows users to monetize their unused internet bandwidth. By installing a browser extension, users securely share bandwidth to help AI companies crawl the web for public data, receiving Points (convertible to crypto tokens) as compensation. They also operate a massive distributed crawler, giving them unique access to high-quality public web data at global scale. They are hiring a Research Crawling Engineer (Full remote - USA/EU 6 hour overlap with EST) You will join a company 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. 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. This Role Involves: - 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 MISSIONS 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 normalisation 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 Example Projects you could work on : - Build a distributed crawler for a continuously updated, high-quality web project - Design a system to classify and filter billions of pages for pretraining - Extract structured data from dynamic, JS-heavy sites at scale - Improve deduplication and quality scoring across multimodal datasets Requirements Strong programming experience in one or more of : Go, Rust, Python, Java, or C++ Experience working for reputable companies Experience building and maintaining large-scale web crawlers or large-scale data pipelines Experience designing high-throughput, fault-tolerant systems for data collection (millions to billions of URLs/day) Experience handling anti-bot systems, rate limits, and dynamic/JS-heavy sites Experience constructing and maintaining datasets for research and model training 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 Preferred / Bonus: 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 Main Evaluation Criteria: 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 Benefits Contract : Permanent role (Full remote - USA or 6 hour overlap with EST). Salary : $150k to $225k based on experience and demonstrated ability to operate at scale + Equity package / tokens Recruitment process : Recruiter / HR Call Technical Interview CEO Interview Final Interview

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