Machine Learning Engineer - Localization Data & AI

Location: Madrid, Spain Work Model: Hybrid - three days per week in the Madrid office. Role: Machine Learning Engineer - Localization Data & AI team Reporting to: Localization Data & AI Manager Responsibilities - Develop scalable and production-ready ML pipelines to support AI-driven localization workflows. - Collaborate with teams to understand needs and translate them into ML solutions. - Train, evaluate, and fine-tune models for NLP, computer vision, and other ML use cases. - Deploy and monitor ML models in different environments, ensuring performance, scalability, and reliability. - Develop preprocessing pipelines tailored to ML/DL tasks using large structured and unstructured datasets in multiple languages. - Apply MLOps best practices for versioning, testing, CI/CD, and monitoring of models (e.g., MLflow, SageMaker, or Vertex AI). - Develop API REST services using languages such as Python, .NET, or Node.js. - Partner with Data Engineers and Data Scientists to ensure efficient data access and optimized feature engineering processes. - Contribute to model and system improvement through experiment tracking, feedback loops, and performance analysis. - Conduct code reviews and ensure high coding standards. - Optimize applications for maximum speed and scalability. - Collaborate with teams to design and ship new features. - Ensure adherence to ethical AI and data governance standards. Qualifications - 2+ years of hands-on experience in Machine Learning Engineering. - Bachelor's degree in Computer Science, Engineering, Applied Mathematics, or a related discipline. - Python programming skills with experience in ML libraries (scikit-learn, TensorFlow, PyTorch, and Hugging Face). - Proficiency in building and deploying ML models in real-world applications. - Familiarity with data processing frameworks (Pandas, NumPy) and orchestration tools (Airflow, Prefect). - Experience with model lifecycle management and MLOps tools (e.g., MLflow, Vertex AI, SageMaker, Azure ML). - Experience working with APIs, RESTful services, and microservice-based architecture. - Knowledge of NLP and computer vision techniques and tools for multilingual data. - Experience with cloud services (AWS, Azure, or GCP) for ML/DL development and deployment. - Experience with WebAPI and RESTful services. - Knowledge of software engineering best practices and tools (GitLab, GitHub), such as Continuous Integration and Version Control. - Experience overseeing and contributing to the infrastructure that powers ML systems (e.g., Terraform) ensuring maintainable and secure foundations for scalable deployment. - Debugging skills and ability to read code fluently. - Ability to translate data insights into business value. Electronic Arts is an equal opportunity employer. All employment decisions are made without regard to race, color, national origin, ancestry, sex, gender, gender identity or expression, sexual orientation, age, genetic information, religion, disability, medical condition, pregnancy, marital status, family status, veteran status, or any other characteristic protected by law. We will also consider employment-qualified applicants with criminal records in accordance with applicable law. EA also makes workplace accommodations for qualified individuals with disabilities as required by applicable law. J-18808-Ljbffr