{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/skill/webapi"},"x-facet":{"type":"skill","slug":"webapi","display":"Webapi","count":1},"x-feed-size-limit":100,"x-feed-sort":"enriched_at desc","x-feed-notice":"This feed contains at most 100 jobs (the most recently enriched). For the full corpus, use the paginated /stats/by-facet endpoint or /search.","x-generator":"yubhub-xml-generator","x-rights":"Free to redistribute with attribution: \"Data by YubHub (https://yubhub.co)\"","x-schema":"Each entry in `jobs` follows https://schema.org/JobPosting. YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_104d9921-154"},"title":"Machine Learning Engineer","description":"<p>Electronic Arts creates next-level entertainment experiences that inspire players and fans around the world. Here, everyone is part of the story. Part of a community that connects across the globe. A place where creativity thrives, new perspectives are invited, and ideas matter. A team where everyone makes play happen.</p>\n<p>We are hiring a Machine Learning Engineer to join our Localization Data &amp; AI team, reporting to the Localization Data &amp; AI Manager. The Loc Data &amp; AI team&#39;s mission is to empower EA Localization through intelligent, data-driven solutions,building scalable AI systems, streamlining ML operations, and creating tools that enhance the quality and efficiency of localized content.</p>\n<p>This role focuses on designing, deploying, and maintaining ML models and infrastructure, collaborating closely with Data Engineers and Data Scientists.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Design, build, and maintain scalable and production-ready ML pipelines to support AI-driven localization workflows.</li>\n<li>Collaborate with cross-functional teams to understand business needs and translate them into ML solutions.</li>\n<li>Train, evaluate, and fine-tune models for NLP, Computer Vision, and other ML use cases.</li>\n<li>Deploy and monitor ML models in different environments, ensuring performance, scalability, and reliability.</li>\n<li>Develop preprocessing pipelines tailored to ML/DL tasks by working with large structured and unstructured datasets in multiple languages.</li>\n<li>Leverage MLOps best practices for versioning, testing, CI/CD, and monitoring of models (e.g., MLflow, Sagemaker, or VertexAI).</li>\n<li>Design, develop, and maintain API REST services using languages such as Python, .NET, and/or Node.js.</li>\n<li>Partner with Data Engineers and Data Scientists to ensure efficient data access and optimized feature engineering processes.</li>\n<li>Contribute to continuous model and system improvement through experiment tracking, feedback loops, and performance analysis.</li>\n<li>Conduct code reviews and ensure high-quality coding standards.</li>\n<li>Optimize applications for maximum speed and scalability.</li>\n<li>Collaborate with cross-functional teams to define, design, and ship new features.</li>\n<li>Ensure adherence to ethical AI and data governance standards.</li>\n</ul>\n<p><strong>Qualifications</strong></p>\n<ul>\n<li>2+ years of hands-on experience in Machine Learning Engineering.</li>\n<li>Bachelor’s degree in Computer Science, Engineering, Applied Mathematics, or related discipline.</li>\n<li>Strong Python programming skills, with experience in ML libraries (scikit-learn, TensorFlow, PyTorch, Hugging Face).</li>\n<li>Proficiency in building and deploying ML models in real-world applications.</li>\n<li>Familiarity with data processing frameworks (Pandas, NumPy) and orchestration tools (Airflow, Prefect).</li>\n<li>Solid understanding of model lifecycle management and MLOps tools (e.g., MLflow, VertexAI, SageMaker, AzureML).</li>\n<li>Experience working with APIs, RESTful services, and microservice-based architecture.</li>\n<li>Knowledge of NLP and Computer vision techniques and tools for multilingual data is a strong plus.</li>\n<li>Experience with cloud services (AWS, Azure, or GCP) for ML/DL development and deployment.</li>\n<li>Experience with WebAPI and RESTful services.</li>\n<li>Knowledge of software engineering best practices and tools (Gitlab and Github), such as Continuous Integration and Version Control (Git).</li>\n<li>Oversee and contribute to the underlying infrastructure that powers ML systems (e.g, Terraform) ensuring robust, maintainable, and secure foundations for scalable deployment.</li>\n<li>Strong debugging skills and fluent in reading code.</li>\n<li>Strong problem-solving skills, and ability to communicate technical concepts clearly with stakeholders.</li>\n<li>Excellent communication and collaboration skills, with the ability to translate data insights into business impact.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_104d9921-154","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Electronic Arts","sameAs":"https://jobs.ea.com","logo":"https://logos.yubhub.co/jobs.ea.com.png"},"x-apply-url":"https://jobs.ea.com/en_US/careers/JobDetail/Machine-Learning-Engineer/213194","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","Machine Learning","NLP","Computer Vision","MLOps","API REST services","Data processing frameworks","Orchestration tools","Model lifecycle management","Cloud services","WebAPI","RESTful services","Software engineering best practices","Terraform"],"x-skills-preferred":[],"datePosted":"2026-04-24T13:14:18.321Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Madrid"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Machine Learning, NLP, Computer Vision, MLOps, API REST services, Data processing frameworks, Orchestration tools, Model lifecycle management, Cloud services, WebAPI, RESTful services, Software engineering best practices, Terraform"}]}