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. Interviews will be conducted via virtual meetings and/or onsite.
it's an invitation to be part of a team that’s bringing AI to have practical benefits to billions globally.
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📌 Application Engineer - Internship H/F (España)
🏢 Bjak
📍 España