Description & Requirements

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

COMPENSATION AND BENEFITS

The ranges listed below are what EA in good faith expects to pay applicants for this role in these locations at the time of this posting. If you reside in a different location, a recruiter will advise on the applicable range and benefits. Pay offered will be determined based on a number of relevant business and candidate factors (e.g. education, qualifications, certifications, experience, skills, geographic location, or business needs).

PAY RANGES

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

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

Pay is just one part of the overall compensation at EA.

In the US, we offer a package of benefits including 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) to regular full-time employees. Certain roles may also be eligible for bonus and equity.

For Canada, we offer a package of benefits including 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 you welcome a new child (12 weeks for maternity, and 4 weeks for parental/adoption leave), extended health/dental/vision coverage, life insurance, disability insurance, retirement plan to regular full-time employees. Certain roles may also be eligible for bonus and equity.

Post To

External careers site, Internal careers site

LinkedInID

1449