Description
Electronic Arts creates immersive entertainment experiences that inspire players and fans worldwide.
Central Technology at EA accelerates creative opportunity and progress, transforming interactive entertainment with cutting-edge technology.
The EA Security team protects players, employees, products, and platforms by setting security standards, assessing risks, and ensuring compliance with global requirements.
As a Machine Learning Engineer III, you will report to the Senior Manager, EA Player Security Data Labs, and work in a hybrid model combining remote work and in-office collaboration.
Your primary focus will be on building and operating production-grade data and machine learning infrastructure to support data scientists and analysts in delivering fraud detection, anti-cheat, and account security solutions across EA games.
Responsibilities
- Design, build, and maintain scalable data ingestion, transformation, and feature pipelines for machine learning workflows in 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.
- Collaborate with data scientists to productionize machine learning models, focusing on data consistency, quality, and reliable 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. Rust experience 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.
Why You Will Enjoy This Role
- Work on data and machine learning systems that protect millions of players from fraud and cheating.
- Operate as a senior individual contributor with strong technical ownership and autonomy.
- Design and build core data infrastructure that powers machine learning across EA Player Security.
Benefits
Electronic Arts offers comprehensive benefits packages tailored to meet local needs, including medical insurance, mental health support, retirement savings, paid time off, family leave, free games, and more.