Machine Learning Engineer
Electronic Arts (EA) · Madrid, Community of Madrid, Spain
- On site
- Full-time
- $130,000 / year
- Madrid, Community of Madrid, Spain
Job highlights
- Design, deploy, maintain ML models and infrastructure.
- Build scalable AI systems for localization.
- Work with NLP and Computer Vision.
- Leverage MLOps and cloud services.
- Collaborate on data-driven localization solutions.
About the role
Machine Learning Engineer - Localization Data & AI
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.
We are hiring a Machine Learning Engineer to join our Localization Data & AI team, reporting to the Localization Data & AI Manager. The Loc Data & AI team'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. This role focuses on designing, deploying, and maintaining ML models and infrastructure, collaborating closely with Data Engineers and Data Scientists.
Responsibilities
- Design, build, and maintain scalable and production-ready ML pipelines to support AI-driven localization workflows.
- Collaborate with cross-functional teams to understand business 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 by working with large structured and unstructured datasets in multiple languages.
- Leverage MLOps best practices for versioning, testing, CI/CD, and monitoring of models (e.g., MLflow, Sagemaker, or VertexAI).
- Design, develop, and maintain API REST services using languages such as Python, .NET, and/or Node.js.
- Partner with Data Engineers and Data Scientists to ensure efficient data access and optimized feature engineering processes.
- Contribute to continuous model and system improvement through experiment tracking, feedback loops, and performance analysis.
- Conduct code reviews and ensure high-quality coding standards.
- Optimize applications for maximum speed and scalability.
- Collaborate with cross-functional teams to define, 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 related discipline.
- Strong Python programming skills, with experience in ML libraries (scikit-learn, TensorFlow, PyTorch, 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).
- Solid understanding of model lifecycle management and MLOps tools (e.g., MLflow, VertexAI, SageMaker, AzureML).
- Experience working with APIs, RESTful services, and microservice-based architecture.
- Knowledge of NLP and Computer vision techniques and tools for multilingual data is a strong plus.
- 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 and Github), such as Continuous Integration and Version Control (Git).
- Oversee and contribute to the underlying infrastructure that powers ML systems (e.g, Terraform) ensuring robust, maintainable, and secure foundations for scalable deployment.
- Strong debugging skills and fluent in reading code.
- Strong problem-solving skills, and ability to communicate technical concepts clearly with stakeholders.
- Excellent communication and collaboration skills, with the ability to translate data insights into business impact.
About Electronic Arts
We’re proud to have an extensive portfolio of games and experiences, locations around the world, and opportunities across EA. We value adaptability, resilience, creativity, and curiosity. From leadership that brings out your potential, to creating space for learning and experimenting, we empower you to do great work and pursue opportunities for growth.
We adopt a holistic approach to our benefits programs, emphasizing physical, emotional, financial, career, and community wellness to support a balanced life. Our packages are tailored to meet local needs and may include healthcare coverage, mental well-being support, retirement savings, paid time off, family leaves, complimentary games, and more. We nurture environments where our teams can always bring their best to what they do.
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.
Key skills/competency
- Machine Learning Engineering
- ML Pipelines
- NLP
- Computer Vision
- MLOps
- Python
- TensorFlow
- PyTorch
- Cloud Services (AWS, Azure, GCP)
- RESTful Services
Skills & topics
- Machine Learning Engineer
- ML Engineer
- AI
- Machine Learning
- Python
- NLP
- Computer Vision
- MLOps
- Cloud Computing
- Data Science
- Software Engineering
- Electronic Arts
- EA
How to get hired
- Tailor your resume: Highlight your 2+ years of ML Engineering experience, Python skills, and familiarity with ML libraries (TensorFlow, PyTorch, scikit-learn, Hugging Face).
- Showcase MLOps proficiency: Emphasize experience with MLflow, VertexAI, SageMaker, or AzureML and CI/CD practices.
- Quantify achievements: Use numbers to demonstrate the impact of your ML solutions, especially in NLP or Computer Vision.
- Demonstrate collaboration: Provide examples of working with cross-functional teams and communicating technical concepts clearly.
- Prepare for technical interviews: Brush up on Python, ML algorithms, data structures, and cloud platforms (AWS, Azure, GCP).
Technical preparation
Behavioral questions
Frequently asked questions
- What are the core responsibilities of a Machine Learning Engineer at Electronic Arts?
- As a Machine Learning Engineer at EA, you'll be responsible for designing, building, and maintaining scalable ML pipelines and models. This includes working with NLP and Computer Vision for AI-driven localization workflows, leveraging MLOps best practices, and deploying/monitoring models in production environments.
- What programming languages and ML libraries are most important for this Machine Learning Engineer role at EA?
- Strong Python programming skills are essential, with hands-on experience in ML libraries such as scikit-learn, TensorFlow, PyTorch, and Hugging Face. Experience with API development using Python, .NET, or Node.js is also valuable.
- Does Electronic Arts provide opportunities for professional growth for Machine Learning Engineers?
- Yes, EA emphasizes continuous learning and experimentation. They encourage employees to pursue opportunities for growth and provide a supportive environment where your potential can be realized, including through hands-on experience with cutting-edge ML technologies.
- What kind of data will a Machine Learning Engineer work with at EA?
- You will work with large structured and unstructured datasets in multiple languages. This involves developing preprocessing pipelines tailored for ML/DL tasks, and partnering with Data Engineers and Data Scientists for efficient data access and feature engineering.
- What are the benefits of working at Electronic Arts as a Machine Learning Engineer?
- EA offers a holistic approach to benefits, focusing on physical, emotional, financial, career, and community wellness. This includes healthcare, mental well-being support, retirement savings, paid time off, family leaves, and access to complimentary games, all within an environment that nurtures creativity and collaboration.
- Is experience with MLOps tools required for the Machine Learning Engineer position at Electronic Arts?
- Yes, a solid understanding of model lifecycle management and MLOps tools is required. Familiarity with tools like MLflow, VertexAI, SageMaker, or AzureML is expected, as you'll be leveraging MLOps best practices for versioning, testing, CI/CD, and monitoring.
- What kind of ML use cases can I expect to work on as a Machine Learning Engineer at EA?
- This role focuses on AI-driven localization workflows. You'll be training, evaluating, and fine-tuning models for NLP, Computer Vision, and other ML use cases relevant to enhancing the quality and efficiency of localized content.