AI Engineer

About the role

Labhouse is a Barcelona-based startup studio building AI-powered mobile apps used by hundreds of thousands of people worldwide. Our products — including Invoice Fly and Summary AI — are designed to make everyday tasks faster, smarter, and simpler through a subscription model that puts the user first.

We were founded by Andrés Bou and Horacio Martos, the duo behind SocialPoint (acquired by Take-Two Interactive), and we operate with the mindset of a product company: small teams, high ownership, and a relentless focus on building things that matter.

Would you like to make an impact as part of a company that builds the best mobile apps used by millions of users worldwide? If so, discover your next challenge below.

THE ROLE

At Labhouse, AI is not a feature — it's the core of what we build. As our AI Engineer, you will own the development, fine-tuning, and productionization of the models that make our apps work at a high level of accuracy and performance.

This is a hands-on engineering role. You will:

- Research, design, and train models suited to the specific needs of our products

- Fine-tune existing open-source and foundation models to maximize accuracy and performance

- Own the full model lifecycle: data curation, experimentation, evaluation, and production deployment

- Collaborate with mobile and backend engineers to integrate models directly into our apps

- Define and track the metrics that drive quality — and continuously push them in the right direction

ABOUT YOU

Academic Background

A strong academic foundation matters to us. We're looking for candidates with a degree in Computer Science, Electrical Engineering, Mathematics, Physics, or a related technical field. A Master's or PhD in machine learning or a related area is a strong plus — but not a requirement if you can demonstrate equivalent depth through your work.

What We Are Looking For

More than years of experience, we care about demonstrated ability to build. You should be able to point to models you've trained, fine-tuned, or shipped — whether in a professional setting, a research context, or on your own. A strong GitHub and/or Hugging Face profile is a significant advantage.

- Hands-on experience training or fine-tuning deep learning models that are used in production.

- Strong Python skills and experience with ML frameworks (PyTorch or JAX preferred)

- Comfort with the full model development cycle: data pipelines, experiment tracking, evaluation, deployment and scaling.

- Solid understanding of modern model architectures and when to apply them

- Experience with the Hugging Face ecosystem (Transformers, Datasets, Hub) is a strong plus

- Ability to work autonomously, make decisions under uncertainty, and ship without waiting for perfect conditions

AI Proficiency

You actively use AI tools in your own workflow — not as a novelty, but as a genuine productivity multiplier. You stay current with the state of the art and know how to apply the latest research to real product problems.