Machine Learning Engineer 3

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.

Central Technology is the force multiplier, accelerating creative opportunity and progress at EA. We’re a world-class community of technologists, innovators, strategists, and orchestrators transforming interactive entertainment. Together, we power the platforms, AI-driven tools, live services, and infrastructure that ensure global scale, secure player experiences, and unlock bold new possibilities.

EA Security protects our players, employees, products, and platforms. We set security standards, support game and enterprise teams, assess risk across partners and systems, and ensure compliance with global requirements. Our work strengthens system integrity, supports fair play, and enables teams to build and operate securely at scale.

The Senior Machine Learning Engineer will report to the Senior Manager, EA Player Security Data Labs. You will follow a hybrid work model with a mix of remote work and in-office collaboration. This role focuses on 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.

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, with a strong focus on data consistency, data 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.

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 demonstrated experience building and maintaining large-scale, production-grade data pipelines. Rust Experience 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

You will work on data and machine learning systems that protect millions of players from fraud and cheating.

You will operate as a senior individual contributor with strong technical ownership and autonomy.

You will design and build core data infrastructure that powers machine learning across EA Player Security.

Why We Are Excited About This Role

We build systems that directly protect player trust and fair play across EA games.

We value strong data engineering fundamentals and production-focused machine learning.

We support senior engineers with autonomy and opportunities to shape long-term technical direction.

Pay Transparency - North America

* British Columbia (depending on location e.g. Vancouver vs. Victoria) *$114,300 - $156,200 CAD

* California (depending on location e.g. Los Angeles vs. San Francisco) *$127,700 - $190,600 USD

* Washington (depending on location e.g. Seattle vs. Spokane) *$122,300 - $158,500 USD