About RankmyAI

RankmyAI is the independent research platform for the AI tool ecosystem. We are an initiative of the Hogeschool van Amsterdam (Centres for Marketing Innovation and Applied AI Expertise). We rank and classify 63,000+ AI tools across traffic, investment, and user reviews, and publish monthly insights on how the AI landscape is evolving. Our work is read by founders, investors, and journalists looking for structured, data-driven analysis.

Our pipeline already runs multi-model classifications and a range of more advanced algorithms. The next phase is to build out the research engine: better taxonomies, smarter data, and signals that nobody else publishes.

The role

You will work directly with the founding team on the platform's research backbone. The work touches four areas, with the first as the primary focus.

1. Taxonomy and classification (primary focus)

Our classification system determines where tools belong across multiple levels of granularity and within several established frameworks running in parallel. You will help us evolve it to maintain consistency and precision as the database continues to grow.

In practice: refining the taxonomy hierarchy based on real classification output, improving prompt design and schema discipline for our multi-model pipeline, and building a feedback loop where manual corrections extend a golden dataset over time. You will also keep our parallel framework taxonomies validated and up to date as the AI ecosystem evolves.

2. New data features

We have a backlog of new variable ideas across trust, pricing, AI-specific characteristics, ecosystem, and compliance. You will pick up the high-impact ones, design how they will be measured, prototype the extraction pipeline, validate quality, and bring them into the platform. Each feature you launch adds a new dimension for comparing AI tools.

3. Discovery of new AI companies

Prototype a classifier that surfaces newly launched AI companies from large external datasets, so we lean less on manual sourcing. Decide which ones belong in our database and how confidence is scored.

4. Insights and signals

Dig into the dataset to surface patterns and anomalies worth publishing. Translate the findings into clear visualisations and short analytical write-ups for our audience.

What we are looking for

• Currently pursuing an MSc or final-year BSc in Computer Science, AI, Data Science, Computational Linguistics, or a related field
• Strong Python: you can build and maintain a production pipeline, not just notebooks
• Practical experience with LLMs and prompt engineering. Bonus if you have worked with structured outputs, JSON schema, or multi-model evaluation
• Comfort with data analysis tooling: pandas, Jupyter, Excel for sanity checks, basic statistics for anomaly detection
• A taste for taxonomy and classification problems: you find label proliferation genuinely annoying and want to fix it
• Clear written English, able to translate research findings into something a non-technical reader can follow

What you get

• Direct ownership of research that goes into a live product with an active audience
• Work across the full lifecycle, from taxonomy design through pipeline, publication, and user feedback
• Mentorship from the founding team
• Flexible hybrid working from our Amsterdam base
• A spot in a research initiative at exactly the moment it is gaining momentum

How to apply

Send us:

• Your CV
• A short note (max one page) on a classification, taxonomy, or data-quality problem you have worked on. What made it hard, and what you would do differently.
• Optional: a link to code, a notebook, a blog post, or anything else that shows how you think.

Apply via email to [email protected] or message David Kakanis on LinkedIn. Questions are welcome at the same channels.