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. It’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, arXiv…)
- 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 €60,000–€90,000 based on the level of your experience
- Bonus/equity program.
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