4+ years of professional experience in technical or scientific writing, preferably in AI or data-related fields.
Strong quantitative literacy to analyze and explain complex research papers.
Proven experience in building and maintaining knowledge bases or documentation systems.
Fluency with LLM tools and a commitment to verifying claims against sources.
Experience with editorial or peer-review processes in technical writing.
Published works such as white papers or technical blog posts.
Familiarity with Markdown, diagrams, and docs-as-code tools; Python skills are a plus.
Responsibilities
Inventory and organize existing research and technical documents, establishing canonical sources.
Build and maintain an internal knowledge base in Google Workspace with an AI layer for citation.
Run internal peer reviews for external technical content, ensuring traceability of claims.
Summarize and assess external research, highlighting critiques and debates relevant to the company's position.
Launch and manage technical publishing efforts, including blog posts and white papers.
Collaborate with Product and Customer Success to create customer-facing documentation and training materials.
Benefits
Onsite work environment in San Francisco.
Opportunity to work closely with the CEO and Chief Science Officer.
Engagement in a meaningful project that shapes the company's knowledge base.
Potential for professional growth in a cutting-edge technology field.
Full Job Description
About the Role
We're hiring a Technical Writer to build the single source of truth for Alembic's science. Our founder and CEO, the inventor behind our core technology, and our Chief Science Officer have produced years of research notes, testing and verification programs, and technical analyses. That work is spread across dozens of documents, and the links between them mostly live in their heads. You'll organize it into a verified, connected knowledge base the whole company can query and trust, run the internal peer review that every external technical claim passes through, and turn the strongest material into white papers and a technical blog.
We'll measure success by how much easier it becomes to find and trust what we know: fewer documents, each one canonical, sourced, and current. This role is onsite in San Francisco and reports to our Chief Science Officer, working day to day with our CEO and closely with Product, Engineering, and Customer Success.
What You'll Do
Inventory our existing research and technical documents, map how they relate, and decide what is canonical, what is superseded, and what is missing.
Build and maintain Alembic's internal knowledge base in Google Workspace, including an AI layer (Gemini and NotebookLM) grounded in curated sources, so answers come back with citations to the documents behind them.
Run internal peer review for external technical content and LLM-assisted drafts: trace each claim to a source, flag what can't be traced, and route open questions to the right scientist.
Assess the external research we build on: summarize each paper's claims, known critiques, and open debates, and how our position holds up against them.
Launch and run Alembic's technical publishing, including blog posts, white papers, and articles drawn from existing material and cleared through review.
Extend the knowledge base into customer-facing documentation and training materials with Product and Customer Success.
What Will Help You Succeed
4+ years writing or editing technical or scientific material professionally, ideally in AI, data, research, or another field where accuracy gets checked.
Quantitative literacy: you can read a machine learning, statistics, or physics paper, explain its assumptions, and say where it is weakest.
Experience building a knowledge base, wiki, or documentation system out of scattered material, including taxonomy, naming, and upkeep.
Fluency with LLM tools, paired with the discipline to verify every claim they produce against a source.
The confidence to question a founder or scientist when a claim isn't supported, and the tact to keep that conversation productive.
Experience with an editorial or peer-review process (journal, research organization, medical or regulatory writing, or a docs team with formal review).
Published technical writing such as white papers, technical blog posts, or long-form articles.
Comfort with diagrams, process flows, Markdown, and docs-as-code tools; Python or scripting is a plus.
Familiarity with causal inference, experimentation, or marketing measurement is a plus.
The role is right for you if:
You've taken a scientist's scattered work and made it usable by an entire company, and you want to do that alongside the inventor of the technology.
You care more about whether a sentence is true than about how many sentences you shipped this week.
