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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Machine Learning Engineer - **Company:** Cloudbeds - **Location:** Spain (Remote available) - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Big Data, Data Validation, Distributed Systems, Github, Python (Programming Language), Machine Learning, Standard Sql, Software Construction, Software Engineering, Strategies of Testing, Performance Testing, Backend, Information Technology, Data Analytics, Machine Learning Operations, Jenkins - **Published:** August 11, 2026 - **Apply:** https://es.trabajo.org/oferta-5355-c7bdab84c8f0559034cd23255c42a9f8 ## About the Role algorithms. We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency. Proven track record in designing, deploying, and maintaining production-grade, distributed ML systems. Apache Airflow, Prefect, Dagster), and model monitoring/drift detection at scale. Software Engineering Rigor: Strong background in Python, distributed systems, and backend development, with a firm grasp of software engineering best practices. Demonstrated ability to influence cross-functional teams, mentor junior talent, and drive consensus on complex technical decisions. Ability to apply statistical and ML methods to optimize revenue management and pricing strategies. 5+ years of experience in a machine learning role, with demonstrated success in ML Engineering and deploying models to production. ~ Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing). ~ Great understanding of machine learning principles (experimental design, statistical distributions and test, machine learning algorithms) ~ Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms. ~ Strong Python programming skills and adherence to software engineering best practices (e.g., Expert-level SQL skills and experience working with large datasets for analysis and modeling. ~ Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges. ~ Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams. ~ Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field. Bonus Skills to Stand Out (Optional): GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment. Experience with data quality monitoring tools and frameworks. Master's or PhD in Computer Science, Mathematics, or a related field. We're 650+ employees across 40+ countries, bringing together elite engineers, AI architects, world-class designers, and hospitality veterans to solve challenges others haven't dared to tackle. Our diverse team speaks 30+ languages, but we all share one language: a passion for innovation and travel. From pioneering breakthroughs in machine learning to revolutionizing how hotels operate, we're not just watching the future of hospitality unfold - we're coding it, designing it, writing it and shipping it. If you're ready to work alongside some of the brightest minds in tech who are obsessed with using AI to transform a trillion-dollar industry, this is your chance to be part of something extraordinary. Learn more online at Company Awards to Check Out Best All-In-One Hotel Management System | HotelTechAwards (2025) Remote First, Remote Always P ## Related Videos - [The Road to MLOps: How Verivox Transitioned to AWS](https://www.wearedevelopers.com/videos/1050-the-road-to-mlops-how-verivox-transitioned-to-aws) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [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)