Machine Learning Engineer III

Electronic Arts is seeking a Machine Learning Engineer III to join their Central Technology team, specifically within the EA Player Security Data Labs. The successful candidate will work on building and operating production-grade data and machine learning infrastructure to support fraud detection, anti-cheat, and account security solutions across EA games.

Responsibilities:

• Design, build, and maintain scalable data ingestion, transformation, and feature pipelines that support machine learning workflows for fraud and anti-cheat systems.
• Own and operate production data and machine learning infrastructure, including batch and near-real-time data processing, feature generation, training workflows, and inference pipelines.
• Partner with data scientists to productionize machine learning models, focusing on data consistency, quality, and reliable offline and online feature computation.
• Ensure data and machine learning pipelines are reliable, repeatable, observable, and cloud-agnostic across environments.
• Contribute to architectural standards, platform design decisions, and engineering best practices as a senior individual contributor.

Qualifications:

• Five or more years of professional experience in data engineering, machine learning engineering, or a closely related role with production ownership.
• Strong proficiency in Python and SQL, with experience building and maintaining large-scale, production-grade data pipelines. Experience with Rust is a plus.
• Experience designing and operating data-intensive systems using modern programming languages, including Rust.
• Hands-on experience supporting end-to-end machine learning workflows, with an emphasis on data preparation, feature pipelines, and model deployment infrastructure.
• Experience working in cloud environments such as AWS or GCP, including large-scale data processing systems.
• Experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Experience with CI/CD systems and production deployment workflows, including GitLab.
• Experience with Terraform and Spark.

Benefits:

• Comprehensive benefits package, including health care services, mental well-being support, retirement savings, paid time off, family leaves, free games, and more.
• Flexible work arrangements, including hybrid work model.
• Opportunities for growth and development within the company.