Hiring nowAI technical writing, education and developer relations

AI Technical Writer

Also called ML Technical Writer

An AI Technical Writer documents AI products with accurate, tested examples and honest limitations. Good documentation helps customers finish real tasks without support, and it protects the company from overclaiming what its models can do.

What they do

The writer turns a product that behaves probabilistically into documentation people can rely on. They work with engineers and product managers to understand new features, then write guides, reference pages and quickstarts. They run every code sample in a notebook or sample application before it ships. They record where outputs vary, where the product fails and what to do about it. They watch support tickets and user sessions to see where readers get stuck. They keep docs versioned alongside releases, retire stale pages and flag changes that break existing examples.

What a strong hire delivers

In the first months, a strong hire gives the company a documentation set that matches the current product. Quickstarts work from a clean setup. Examples are tested and kept in a repository. Known limitations are stated plainly. Support gets a clear view of which pages cause confusion, and engineers get a repeatable way to review docs before each release.

How you can tell they are good

Ask for documentation they wrote for a technical product and how they checked it was correct. Strong candidates show examples they ran themselves and explain what readers did with the page. Ask how they would document unpredictable output. Be wary of polished prose with no testing, or of someone who copies vendor claims without checking them.

Why it is hard to fill

Titles vary, and many candidates are really software engineers, teachers or support specialists who happen to write. The mix of writing craft, code fluency and sceptical testing is uncommon. Good people often sit in developer tools companies and are not looking. Portfolios are often private, so you have to ask for samples and talk through the method behind them.

Where to find them

Look at technical writers from developer tools, cloud and data platforms, and API-first software companies. Also look at developer educators, solutions engineers, support engineers who write documentation, and teachers who moved into software. Some come from open source documentation work. Machine learning practitioners with a strong writing habit can work too, if they care about readers.

Indicative pay

Not enough published evidence yet to give a fair range for this role, which is common for work this new. We benchmark it for you as part of a search.

Interview questions for an AI Technical Writer

  1. Tell us about documentation you wrote for a technical product. How did you know it was accurate?

    Strong answers describe running the code, reviewing with engineers and checking against the live product. They mention reader feedback or task success. Worry if accuracy rests on trusting the engineer's word or on a single read-through.

  2. How would you document a feature whose output changes between runs?

    Look for showing representative outputs, explaining variation, setting expectations and giving ways to check results. They should avoid implying certainty. Worry if they hide the variability or only show the best output.

4 more questions, with what a strong answer covers, are in the Role Kit.

Job description you can post

We build AI products that developers and practitioners use to get real work done. We need a technical writer to make our documentation accurate, tested and honest about limits, so customers can finish their tasks without waiting for help.

What you will do

  • Write quickstarts, guides and reference documentation for our AI products
  • Build and run tested code examples and sample applications
  • Document limitations, failure modes and variable behaviour clearly
  • Work with engineers and product to review docs before each release
  • Keep documentation versioned and retire outdated pages
  • Use support data and user feedback to find and fix unclear content

What you will bring

  • Published documentation or tutorials for a technical product
  • Working Python, shown through examples you have written and run
  • Evidence of testing your own examples before publishing
  • Clear writing for developers of mixed experience
  • Experience gathering feedback from readers or users
  • Ability to challenge unsupported claims politely

Nice to have

  • Experience with notebooks and documentation systems
  • Experience running workshops or training sessions
  • Background in machine learning or data work

Free to use and adapt. If it saves you time, a link back to this page is appreciated.

Skills that matter

  • Technical communicationAdvancedExplain evidence and limitations to relevant readers
  • Change management and trainingAdvancedSupport adoption through learning and organisational change
  • User researchWorkingStudy user needs, context and behaviour
  • PythonWorkingDevelop tested numerical and data software

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How we wrote this

Role definitions are our own editorial work, checked against occupational classifications, standards, research and employer pages. Titles vary by company, and this is a description of the work, not a job advert.

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