Software Engineering & Data Science Documents Wanted - Paid Per Page (English Only)

We are building a licensed library of real, human-written technical documents in software engineering and data science, and we pay contributors per page. If you write long-form technical documents as part of your job, you can turn work you already own into income. WHAT WE PAY Up to $2 USD per page of verified human writing. Payment is based on the number of qualifying pages we accept after review, so larger contributions earn more. Milestones are agreed in advance and paid through Upwork. HOW IT WORKS 1. Tell us what document types you can share and roughly how many pages. 2. Upload your documents (we provide a secure upload link once you are onboarded). 3. Confirm you own the documents and that the writing is human-written, not AI-generated. 4. We review for the criteria below and pay per accepted page. WHAT WE ARE LOOKING FOR We want substantive, professionally written technical documents, not presentations or decks. Preferred format is .docx, although text-native PDFs and Markdown are acceptable. The ideal documents are: - Primarily prose, tables, and native charts or diagrams - Dense and substantive, roughly 250+ words per page - Mostly selectable/extractable text, not screenshots or scanned pages - Restrained, professional formatting typical of internal engineering documentation Software engineering examples: design documents and RFCs, architecture decision records, system and API design specifications, technical specifications, migration plans, runbooks and operational guides, postmortems and incident reviews, performance and scalability analyses, security design reviews and threat models, platform and infrastructure documentation, engineering standards and best-practice guides. Data science and machine learning examples: model documentation and model cards, experiment design and analysis write-ups, A/B test and causal inference reports, evaluation and benchmarking reports, feature engineering and data pipeline specifications, data quality and validation reports, data dictionaries and schema/contract documentation, ML system design documents, analytics deep dives, and research memos. WHAT WE EXCLUDE - Slide decks or presentation-style PDFs - Image-heavy or highly designed marketing materials - Documents dominated by photos, large graphics, or decorative colors - Scans with little extractable text - Raw source code files or notebooks with little written explanation - Forms, flyers, brochures, and one-page promotional material LANGUAGE: STRICTLY ENGLISH ONLY Every document must be written entirely in English. We cannot accept: - Documents in any other language - Bilingual, translated, or mixed-language documents - Otherwise-English documents that contain any non-English text anywhere, including headers, footers, cover pages, letterheads, stamps, watermarks, table labels, chart axis labels, captions, footnotes, appendices, or signature blocks - Non-English company boilerplate, disclaimers, or template text - Non-English file names or metadata If a document contains any visible non-English wording or signage, it will be rejected. Please check the whole file, including the last pages, before submitting. WHO WE ARE INVITING We welcome contributors from anywhere in the world. Your own location and nationality do not matter at all; the only requirement is that the documents themselves are strictly in English. We would especially like to hear from: - Software engineers, senior/staff/principal engineers, and tech leads who write design docs and RFCs - Software and solution architects - Platform, infrastructure, DevOps, and site reliability engineers who write runbooks, reliability reviews, and postmortems - Data scientists, machine learning engineers, and applied researchers - Data engineers and analytics engineers who document pipelines, schemas, and data contracts - MLOps and AI platform engineers - Security engineers who write threat models and design reviews - Engineering and data science managers who write technical strategy and planning documents - QA and test engineers who write test strategies and test plans - Technical writers and documentation specialists on software or data teams - Academics and industry researchers in computer science, statistics, and machine learning with report-style (not slide-style) output RIGHTS AND CONFIDENTIALITY Only submit documents you personally own or have clear written permission to share. Do not submit anything confidential, client-privileged, export-controlled, or covered by an NDA. Remove or redact personal data, client names, credentials, internal hostnames, and anything you are not permitted to share. You will be asked to confirm rights for every file. HOW TO APPLY Please include in your proposal: 1. The document types you can provide 2. Approximate total page count available now 3. Format (.docx, text-native PDF, or Markdown) 4. Confirmation that the content is 100% English and human-written 5. Confirmation that you hold the rights to share it A short redacted sample of 1-2 pages helps us reply faster. Ongoing work is available for contributors whose documents pass review.