# AI Engineer at Labhouse > Remote · Spain · Unspecified · ML / AI · open. Source: https://alderhq.app/jobs/ashby%3Alabhouse%3A8e17d45f-415c-4e18-9b07-44b0261e3765 (read 2026-11-13). ## Facts (observed) - Company: [Labhouse](https://alderhq.app/companies/labhouse) - Location text: Barcelona; Spain (Remote) - Where it can be done from (inferred): Remote · Spain (evidence: "Remote role open worldwide") - Posted: 2026-06-05 (161 days ago) - First seen by alder: 2026-11-07 · last verified: 2026-11-08 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/labhouse/8e17d45f-415c-4e18-9b07-44b0261e3765 - Skills listed (inferred): Python, PyTorch ## Pay and sponsorship - Posted pay: not posted - Market band for similar posted roles (Barcelona, n 5): p25 €85k, median €85k, p75 €138k ## Description (the employer's text) 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. ### Communication You communicate clearly and directly. You can explain technical decisions to non-technical stakeholders, flag blockers early, and collaborate effectively in a small, fast-moving team. ### Nice to Have Experience across multiple model domains (vision, audio, NLP, multimodal) Familiarity with on-device or edge inference optimization (quantization, distillation, ONNX) Experience integrating ML models into mobile or production environments Published research or open-source contributions in ML ### What We Offer Attractive compensation, above market average Hybrid work model based in Barcelona High ownership from day one — you define the direction, not just execute on it Work directly with the founders and a senior, low-ego team A real product with real users — your work will have immediate, measurable impact ### Hiring Process Initial Interview: Meet with our Talent Acquisition Lead to discuss your background and fit for the role. We’ll also ask you to share your proudest projects. Hiring Manager Interview: A deep dive into your experience and leadership capabilities. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Alabhouse%3A8e17d45f-415c-4e18-9b07-44b0261e3765 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.