Machine Learning Engineer III

Electronic Arts is a renowned entertainment company that develops exceptional gaming experiences, boasting a vast international community of players and fans. At EA, creativity thrives, diverse perspectives are welcomed, and ideas matter.

Central Technology at EA accelerates creative opportunity and progress, acting as a force multiplier. This world-class community of technologists, innovators, strategists, and orchestrators transforms interactive entertainment. They power platforms, AI-driven tools, live services, and infrastructure that ensure global scale, secure player experiences, and unlock new possibilities.

The EA Security team protects players, employees, products, and platforms by setting security standards, supporting game and enterprise teams, assessing risk, and ensuring compliance with global requirements. Their work strengthens system integrity, supports fair play, and enables teams to build and operate securely at scale.

As a Machine Learning Engineer III, you will report to the Senior Manager of EA Player Security Data Labs and follow a hybrid work model with remote and in-office collaboration. Your primary focus will be building and operating production-grade data and machine learning infrastructure that enables data scientists and analysts to deliver fraud detection, anti-cheat, and account security solutions across EA games.

Key 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.
• Collaborate 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 within EA Player Security Data Labs.

Requirements:

• 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 demonstrated 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: In the US, benefits include paid time off (3 weeks per year to start), 80 hours per year of sick time, 16 paid company holidays per year, 10 weeks paid time off to bond with baby, medical/dental/vision insurance, life insurance, disability insurance, and 401(k) for regular full-time employees. Certain roles may also be eligible for bonus and other incentive programs.

In Canada, benefits include vacation (3 weeks per year to start), 10 days per year of sick time, paid top-up to EI/QPIP benefits up to 100% of base salary when welcoming a new child, extended health/dental/vision coverage, life insurance, disability insurance, retirement plan for regular full-time employees. Certain roles may also be eligible for bonus and other incentive programs.

Salary ranges:

• British Columbia: $114,300 - $156,200 CAD
• Washington: $122,300 - $158,500 USD