> Markdown version of [/jobs/ext/2093101-machine-learning-engineer-genai-nlp](https://www.wearedevelopers.com/jobs/ext/2093101-machine-learning-engineer-genai-nlp). 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 (Genai & Nlp) - **Company:** Capitole - **Location:** Córdoba, Spain - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Continuous Integration, Python (Programming Language), Machine Learning, 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-genai-nlp-en-cordoba-ID-367535593 ## About the Role Brings3-5 yearsof experience buildingproduction features/systems with AI/ML. Writesadvanced, production-grade Python- not notebook scripting. Has worked onreal NLP / GenAI / LLM projectsand can explain them in depth - embeddings, evaluation metrics beyond accuracy, how they assessed system performance. Thinks like anML engineer: moves models to production, understands the full pipeline, applies solid coding practices (Git, PR, CI/CD, Docker). Knows their way aroundML libraries(scikit-learn, PyTorch) anddata processing(pandas). ?Nice to have: Experience withDatabricks. Familiarity withAWS infrastructure(S3, Lambda, Bedrock). Understanding ofdata augmentation, bias and training pipelines. ASoftware Engineeringbackground 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). ## Description ? Capitole keeps growing - and we want to do it with you!? We're looking for anAI/ML Engineerto join a global leader in HR technology - a teambuilding Generative AI assistantsused across global markets.This is ahands-on engineering role, where focus isshipping GenAI/NLP models to productioninPython, 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:Buildingproduction-ready GenAI/LLM features- chatbot assistants and NLP systems, from prototype to production.Writingstructured, quality Pythonwith real engineering discipline:PR practices, Git, CI/CD, Docker.Designingend-to-end NLP pipelines- data processing, model development, evaluation, deployment.Getting hands-on withLLMs, embeddings and modern GenAI tooling(OpenAI, AWS Bedrock).?We're looking for someone who:Brings3-5 yearsof experience buildingproduction features/systems with AI/ML.Writesadvanced, production-grade Python- not notebook scripting.Has worked onreal NLP / GenAI / LLM projectsand can explain them in depth - embeddings, evaluation metrics beyond accuracy, how they assessed system performance.Thinks like anML engineer: moves models to production, understands the full pipeline, applies solid coding practices (Git, PR, CI/CD, Docker).Knows their way aroundML libraries(scikit-learn, PyTorch) anddata processing(pandas).?Nice to have:Experience withDatabricks.Familiarity withAWS infrastructure(S3, Lambda, Bedrock).Understanding ofdata augmentation, bias and training pipelines.ASoftware Engineeringbackground 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).?Why CAPITOLE?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.??Private health insurance fully paid by Capitole.? ??Flexible compensation: meal, transport and/or childcare vouchers.?WellHub (Gymforless).?Discounts on major brands for employees (Club Capitole).??Don't know us yet?Come discover us!(/) ?See what people say about us ? Glassdoor ()Capitole | Empowering people, unlocking technology innovation ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [How E.On productionizes its AI model & Implementation of Secure Generative AI.](https://www.wearedevelopers.com/videos/623-how-e-on-productionizes-its-ai-model-implementation-of-secure-generative-ai) - [Getting to Know Your Legacy (System) with AI-Driven Software Archeology](https://www.wearedevelopers.com/videos/1437-getting-to-know-your-legacy-system-with-ai-driven-software-archeology) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)