Electronic Arts

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 thoughtful, data-driven solutions. These solutions involve building scalable AI systems, streamlining ML operations, and creating tools that enhance the quality and efficiency of localized content.

You will focus on designing ML models and infrastructure, collaborating with Data Engineers and Data Scientists.

Responsibilities

• You will develop scalable and production-ready ML pipelines to support AI-driven localization workflows.
• You will collaborate with teams to understand needs and translate them into ML solutions.
• You will train, evaluate, and fine-tune models for NLP, Computer Vision, and other ML use cases.
• You will deploy and monitor ML models in different environments, ensuring performance, scalability, and reliability.
• You will develop preprocessing pipelines tailored to ML/DL tasks by working with large structured and unstructured datasets in multiple languages.
• You will use MLOps best practices for versioning, testing, CI/CD, and monitoring of models (e.g., MLflow, Sagemaker, or VertexAI).
• You will develop API REST services using languages such as Python, .NET, or Node.js.
• You will partner with Data Engineers and Data Scientists to ensure efficient data access and optimized feature engineering processes.
• You will contribute to model and system improvement through experiment tracking, feedback loops, and performance analysis.
• You will conduct code reviews and ensure high coding standards.
• You will optimize applications for maximum speed and scalability.
• You will collaborate with teams to design, and ship new features.
• You will 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.
• 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, VertexAI, SageMaker, and AzureML).
• 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 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, maintainable, and secure foundations for scalable deployment.
• Debugging skills and fluent in reading code.
• Translate data insights into revenue .