> Markdown version of [/jobs/ext/3698795-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/3698795-machine-learning-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Machine Learning Engineer

- **Company:** Capitole
- **Location:** Toledo, Spain
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Continuous Integration, Python (Programming Language), Machine Learning, OpenAI, Software Engineering, Data Processing, Pytorch, Large Language Models, Generative AI, Git, Pandas, AutoML, Scikit Learn, Data Augmentation, Docker, Databricks
- **Published:** October 12, 2026
- **Apply:** https://www.buscojobs.com.es/machine-learning-engineer-en-toledo-ID-374196917

## About the Role

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., English C1 (Fluent, all team communication is in English).

## Description

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 global 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.Flexible working hours to balance your professional and personal life.Flexible compensation: meal, transport and/or childcare vouchers.Discounts on major brands for employees (Club Capitole).Capitole | Empowering people, unlocking technology innovation