LLM Data Researcher

What we need

• Research depth in LLMs. A PhD, or a research record that does the same job, in machine learning or NLP. Close to finishing counts.
• You have post-trained and evaluated models yourself, beyond reading the papers. You know where evaluations go wrong, and you have built ones that hold up anyway.
• You move fast. You run the experiment early and write up what you found, including when it is the opposite of what you hoped.
• You can explain it. To a researcher, to an operations lead and to a client.
• AI native. You already work with AI tools and coding agents daily, and you build what you need without waiting for anyone to show you.
• Professional English, used daily with the team and with clients.

• Based in Barcelona, or moving here. The role is on-site with the team, and Sovrano helps with the move.

The next generation of models will be shaped by knowledge that cannot be scraped: the judgment of the lawyers, doctors, engineers and tax advisors who do the work. Sovrano turns that judgment into post-training data, rubrics and benchmarks. This role answers, with evidence, whether that data makes models better, and then tells the team what to do about it. Sovrano AI is a data and research lab in Barcelona. Sovrano brings real experts into building AI: they do the work, Sovrano captures their judgment, and turns it into the data, benchmarks and evidence that frontier AI labs, robotics companies and enterprise AI teams use to train and evaluate their models. Behind it sit a network of 400,000 or more professionals, 100 or more partner universities across Europe, EFMD certification, 23 languages and EuroExec, Sovrano's own benchmark. The internet has been read. The gains now come from post-training and evaluation on expert work, and whoever defines what good work looks like is shaping the frontier. Europe has the experts, the universities and the research talent to build that layer, and too many of its best machine learning researchers leave to do frontier work elsewhere. This is a founding seat on the research team that intends to build it here. The week is about 80 percent research: training, evaluating, publishing. The other 20 percent is communication and coordination, with clients, with marketing and with the data team. You report to Pau Arnal, Founding Researcher, who leads the research team and sets its agenda, and you work directly with him and with the CEO. Said plainly: scope moves as results and clients come in. Some weeks you train models all week, some weeks you are on a call explaining why a data spec should change. Much of the research infrastructure you need is yours to build. The trade is ownership most researchers wait a decade for: a research agenda that is genuinely yours to shape, and results that change what the company does the following week.

What you own

• Proving the data works. Post-train models on Sovrano's datasets and measure the lift. When the data is not pulling its weight, find out why and say so plainly, because that call decides what the experts work on next.
• The benchmarks. Design and run evaluations of frontier LLMs on expert domains. You decide what a fair test looks like, and you defend it.
• Training the models. Pick the method each question needs, and run it end to end.
• The next dataset spec. Your results become dataset specs. You work with the data team so your feedback shapes how data gets made, and you verify the quality of what ships.
• Sovrano's read on the field. Your view of where post-training and evaluation are going shapes what Sovrano takes to market and what it tells the labs.
• Explaining the evidence. When a lab asks what the data does, your results are the answer, explained to a researcher, an operations lead and a client.
• Publishing. Papers at top venues, public benchmarks, blog posts. Your name goes on the work, and the work goes out in public.