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Job Description
Paperpile runs on data at scale, with a literature database of 250M+ academic papers and a growing body of user data accumulated over more than a decade. You'll work across the systems that ingest, process, store, and serve this data reliably: building pipelines, optimizing search, handling PDFs at scale, and exposing clean APIs. Requirements Strong backend engineering background with experience building and operating data-heavy systems in production. Experience deploying and operating services on AWS. Experience designing and maintaining data ingestion pipelines handling messy, heterogeneous sources. Comfortable with web scraping and working with third-party data sources and APIs. Familiarity with Node.js and TypeScript. Itâ's fine if you come from a different background, such as Java or Python, but you should be comfortable working in this environment. High standards for data quality. You think carefully about correctness, deduplication, and consistency. Solid understanding of full-text search systems including indexing strategy, relevance tuning, and query optimization. Proficient in building reliable REST APIs. More useful experience Familiarity with academic publishing formats and data sources (PubMed, Crossref, arXivâ...) Experience with PDF processing pipelines (extraction, transformation, storage and delivery at scale). Experience with LLM-based document processing or ML pipelines for extracting structured data from unstructured text. Large scale web crawling and scraping. Compensation Base compensation â60,000â-â90,000 based on the level of your experience Bonus/equity program.
