> Markdown version of [/jobs/ext/3072271-ai-ml-engineer](https://www.wearedevelopers.com/jobs/ext/3072271-ai-ml-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). --- # Ai/Ml Engineer - **Company:** Pythian - **Location:** Spain (Remote available) - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Python (Programming Language), Machine Learning, Tensorflow, Data Logging, Google Cloud, Pytorch, Large Language Models, Generative AI, Scikit Learn, Kubernetes, Information Technology, Low Latency, Machine Learning Operations, Software Version Control, Docker - **Published:** September 25, 2026 - **Apply:** https://www.buscojobs.com.es/ai-ml-engineer-en-espana-ID-373145591 ## About the Role or Master's degree in Computer Science, Engineering, AI or related quantitative field4 to 5 years of experience in ML engineering or ML/AI-focused software development1-3 years experience with ADK or other agentic frameworksStrong Python programming skillsExperience with ML frameworks (TensorFlow, PyTorch, Scikit-learn)Hands-on experience deploying/pre-trained models (LLMs/Generative AI) into productionCloud platform experience (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes)Solid knowledge of Data Engineering, ETL/ELT, and GitExperience with Kubeflow or managed ML toolsExperience building/scaling AI/ML systemsFamiliarity with MLOps practices (monitoring, logging, CI/CD)Strong communication and cross-functional collaboration skillsStrong communicationTeam collaboration across cross-functional teamsProblem-solving orientationPythonTensorFlowPyTorch ## Description OverviewAs an AI/ML Engineer at Pythian, you design, build, and maintain scalable AI/ML pipelines for client and internal use.You deploy and optimize models, including LLMs and Generative AI, across production environments and cloud platforms.You collaborate with data scientists and software engineers to deliver production-ready AI systems, emphasizing performance, cost-efficiency, and maintainability.This role combines hands-on engineering with shaping AI solutions for transformative outcomes within a cloud-focused services company.Compensaciones / Beneficioscompetitive total rewardsremote work optionstraining allowance and professional development dayswellness budgetpaid vacation and sick dayscharitable volunteering dayResponsabilidadesDevelop, deploy, and maintain AI/ML pipelines for internal and client-driven projectsDeploy, manage, and scale AI models (LLMs and custom models) into productionTranslate model prototypes into scalable, production-ready AI systemsOptimize model performance, latency, and cost on cloud platformsIntegrate AI/ML solutions with AWS, GCP, Azure and use Docker/Kubernetes for consistent deploymentApply MLOps practices: CI/CD, model versioning, monitoring, maintenanceCoordinate with software engineers to embed AI capabilities into applications and workflowsStay updated on AI/ML tech, Generative AI, and MLOps deployment strategiesRequisitos principalesBachelor's or Master's degree in Computer Science, Engineering, AI or related quantitative field4 to 5 years of experience in ML engineering or ML/AI-focused software development1-3 years experience with ADK or other agentic frameworksStrong Python programming skillsExperience with ML frameworks (TensorFlow, PyTorch, Scikit-learn)Hands-on experience deploying/pre-trained models (LLMs/Generative AI) into productionCloud platform experience (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes)Solid knowledge of Data Engineering, ETL/ELT, and GitExperience with Kubeflow or managed ML toolsExperience building/scaling AI/ML systemsFamiliarity with MLOps practices (monitoring, logging, CI/CD)Strong communication and cross-functional collaboration skillsStrong communicationTeam collaboration across cross-functional teamsProblem-solving orientationPythonTensorFlowPyTorch ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Microservices: how to get started with Spring Boot and Kubernetes](https://www.wearedevelopers.com/videos/242-microservices-how-to-get-started-with-spring-boot-and-kubernetes) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Got AI ideas but no money? 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