About Us
Alembic is the pioneering Causal AI platform. We help the worlds largest enterprises move past correlation to prove what actually drives business outcomes - the question marketing and growth teams have never been able to answer with confidence. Fortune 100 companies including Nvidia, Delta Air Lines, and Mars use Alembic to make multimillion-dollar decisions on trusted, causal evidence.
Were backed by a $145M Series B from WndrCo (founded by Jeffrey Katzenberg), Jensen Huang, Joe Montana, Prysm Capital, and Accenture. Our models run on our own NVIDIA DGX SuperPOD built on Grace Blackwell infrastructure - one of the fastest private supercomputers in the world. (Weve melted GPUs getting here.)
About the Role
Were hiring a Technical Writer to build the single source of truth for Alembics 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. Youll 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.
Well 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 Youll 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Inventory our existing research and technical documents, map how they relate, and decide what is canonical, what is superseded, and what is missing.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 Alembics 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 cant be traced, and route open questions to the right scientist.
Assess the external research we build on: summarize each papers claims, known critiques, and open debates, and how our position holds up against them.
Launch and run Alembics 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 isnt 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:
Youve taken a scientists 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.
Why You Might Be Excited About Alembic
In the room with the inventor: Youll work directly with our founder and CEO and our Chief Science Officer on next-generation attribution models grounded in mathematical physics.
Build the foundation: Youll define how Alembic stores, reviews, and publishes what it knows, from the knowledge architecture and review standard to the technical blog.
A science story with proof behind it: Causal AI running on our own NVIDIA DGX SuperPOD on Grace Blackwell infrastructure, one of the fastest private supercomputers in the world.
Accuracy that matters: Fortune 100 companies including Nvidia, Delta Air Lines, and Mars make multimillion-dollar decisions on this work.
Series B momentum, real ownership: Meaningful equity at a Series B company thats raised $145M, with proven product-market fit and Fortune 100 traction.
Why You Might Not Be Excited
You measure your output in pages published. Here, merging three overlapping documents into one may be your best work of the week.
You want a finished style guide, toolchain, and review process on day one. Youll build them.
You prefer writing from finished specs to sitting with a scientist, interrogating rough notes, and pushing back when a claim isnt supported.
| Location | San Francisco, CA |
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