You will own problems end-to-end, from shaping model behavior, to building the systems around it, to ensuring it performs reliably in production. This role sits at the intersection of machine learning, systems, and product, focusing on making AI actually work for users, not just in demos, but in real-world usage. Build and ship AI features end-to-end (model → system → user experience) Debug issues across the full stack (model, orchestration, infra, UX) Develop lightweight evaluation frameworks to measure real-world performance Work closely with product and engineering to translate ambiguous problems into working systems Python PyTorch / JAX Strong foundation in machine learning and modern neural network architectures.

Hands-on experience with training, fine-tuning, or deploying ML models Ability to write clean, production-quality code Data pipelines, training loops, and inference systems are robust, reproducible, and maintainable. Collaborates effectively with engineers, product, and research teams to deliver reliable ML-powered features. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning.

📌 Application Engineer - Home Office (Madrid)
🏢 ActAI
📍 Madrid