Machine Learning Engineer (Madrid)

Machine Learning Engineer (Madrid)

27 sep
|
Capitole
|
Madrid

27 sep

Capitole

Madrid

Capitole keeps growing — and we want to do it with you
We're looking for an Machine Learning Engineer #MLEto join a global leader in HR technology, a team building Generative AI assistants used across general markets.
This is a hands-on engineering role, where focus is shipping GenAI/NLP models to production in Python, working shoulder-to-shoulder with MLEs inside a lean 5–6 person squad across 3–4 projects. If you code your ML solutions yourself rather than leaning on out-of-the-box AutoML tools, and you like owning the technical solution end-to-end, this is for you.
What you'll find here:
Building production-ready GenAI/LLM features (chatbot assistants and NLP systems, from prototype to production).
Writing structured, quality Python with real engineering discipline: PR practices, Git, CI/CD, Docker.
Getting hands-on with LLMs, embeddings and modern GenAI tooling (OpenAI, AWS Bedrock).
We're looking for someone who:
Brings 3–5 years of experience building production features/systems with AI/ML.
Writes advanced, production-grade Python — not notebook scripting.




Has worked on real NLP / GenAI / LLM projects and can explain them in depth (embeddings, evaluation metrics beyond accuracy, how they assessed system performance).
Thinks like an ML engineer: moves models to production, understands the full pipeline, applies solid coding practices (Git, PR, CI/CD, Docker).
Knows their way around ML libraries (scikit-learn, PyTorch) and data processing (pandas).
Nice to have:
Experience with Databricks.
Familiarity with AWS infrastructure (S3, Lambda, Bedrock).
Understanding of data augmentation, bias and training pipelines.
A Software Engineering background with a recent move into AI/ML.
Location:
Barcelona. (Hybrid: 1–2 days in the office).
Language:
English C1 (Fluent, all team communication is in English).
An individual training budget of €1,200 for whatever you choose: events, books, certifications or courses.
Monthly check-ins with your team for continuous feedback.
Flex

📌 Machine Learning Engineer (Madrid)
🏢 Capitole
📍 Madrid

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