Applied Research Scientist [Machine Visibility]

This a Full Remote job, the offer is available from: Europe

Build the research function at Prerender — on a dataset no one else has.

Prerender is a dynamic rendering SaaS that makes websites visible to machines — search crawlers, AI bots, and autonomous agents. Since 2017, thousands of companies have relied on our platform, which serves over 2.7 billion unique pages to web crawlers. We're part of saas.group.

The web is being reshaped by machines — crawlers, LLMs, agents — and no one fully understands how. We're sitting on the data to study it, and we're working to define a new category we call machine visibility: the discipline of ensuring websites are fully accessible to the automated systems navigating the web. This role is central to that effort.

The Opportunity

You'll be Prerender's first dedicated researcher, working directly with the CEO — not just reporting, but actively brainstorming, exploring questions, and shaping the research agenda together.

The starting point: billions of rendered pages and crawl data spanning dozens of bot types. This data exists but hasn't been organized for systematic research. You'll build the data infrastructure that makes rigorous research possible, then use it to produce work no one else can.

There's no existing research team, no inherited methodology, no playbook. You'll build it all.

Some of the questions waiting to be studied:

• How do GPTBot, ClaudeBot, PerplexityBot, and other AI crawlers actually behave in production — and how do agentic sessions differ from passive crawlers?

• What patterns predict whether a page will be visible to an LLM versus a traditional search crawler?

• How is the ecosystem of web-crawling bots evolving, and what does that mean for how the web gets built?

• What does "machine-readable" actually mean when the machines are large language models?

These are open questions. The data to answer them exists. The researcher doesn't — yet.

What You'll Do

Build the Research Infrastructure

Organize, clean, and structure Prerender's existing data for systematic analysis. Design and build new data collection streams to answer questions the current data can't. Create the foundation that makes a sustained cadence of original research possible.

Conduct and Publish Original Research

Design and execute studies using Prerender's data, web-scale datasets, and primary research methods. Own the full research lifecycle: question framing, methodology, analysis, and findings. Produce work ranging from quick data snapshots to in-depth flagship studies — all published under your name.

You'll build deep domain expertise along the way: profiling crawler behavior at scale by bot type, maintaining a living behavioral taxonomy of known and emerging bots (GPTBot, ClaudeBot, PerplexityBot, and whatever ships next), and tracking the frontier — bot documentation changes, LLMs.txt adoption, schema evolution, and published research.

AI is both a subject and a tool in this role. You'll research how LLMs crawl, how AI search systems behave, and how autonomous agents interact with web content, while using AI tools to accelerate your own analysis, synthesis, and pattern recognition.

Inform Business Decisions

Bring data to the conversations that shape what Prerender builds, how we sell, and where we invest. Work across Product, Engineering, Marketing, Sales, and leadership to replace assumptions with evidence.

Who You Are

• Rigorous and deeply curious — you care about getting it right and keep pulling the thread when the first answer comes too easily.

• Technically self-sufficient — you've built your own data pipelines, wrangled messy datasets, and written the code to get from raw data to analysis.

• Independent — you set your own agenda and do your best work with autonomy.

• A clear writer — you turn complex findings into something a non-researcher can act on.

• Honest — you follow the data, including when it's inconvenient.

What You Bring

Required

• Published original research — whether in academia or industry, you've taken a question from hypothesis through methodology to defensible conclusions.

• Hands-on large-scale data analysis — you've queried production data independently, not just read dashboards. Proficient in SQL and Python.

• Strong experiment design — hypothesis formulation, variable isolation, statistical validation, outcome measurement.

• Experience building data infrastructure — not just analyzing pre-built datasets.

• Comfort with AI tools — you're already using them in your research workflows.

Nice to Have

• Direct experience observing AI crawler behavior in production environments

• Hands-on experience with technical SEO (crawlability, rendering, indexing, structured data)

• Familiarity with Answer Engine Optimization (AEO) or Generative Engine Optimization (GEO)

• Published or spoken publicly on machine visibility topics

• Background in information retrieval or NLP

We're looking for someone whose core strength is research