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# Machine Learning Engineer, Hibrido

- **Company:** Capitole
- **Location:** Vitoria-Gasteiz, Spain
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Continuous Integration, Python (Programming Language), Machine Learning, Software Engineering, Data Processing, Pytorch, Large Language Models, Generative AI, Git, Pandas, Scikit Learn, Docker
- **Published:** August 16, 2026
- **Apply:** https://www.buscojobs.com.es/machine-learning-engineer-hibrido-en-vitoria-ID-367559850

## About the Role

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.
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 .
Designing end-to-end NLP pipelines - data processing, model development, evaluation, deployment.
Getting hands-on with LLMs, embeddings and modern GenAI tooling (OpenAI, AWS Bedrock).
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).
? 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.
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.
Flexible working hours to balance your professional and personal life.

## Description

We're looking for an AI/ML Engineer to 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.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 .Designing end-to-end NLP pipelines - data processing, model development, evaluation, deployment.Getting hands-on with LLMs, embeddings and modern GenAI tooling (OpenAI, AWS Bedrock).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).? 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.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.Flexible working hours to balance your professional and personal life.??Private health insurance fully paid by Capitole.??Discounts on major brands for employees (Club Capitole).?Capitole | Empowering people, unlocking technology innovation