Machine Learning Engineer III

Locations

• Kirkland, Washington, United States of America
• Vancouver, British Columbia, Canada
• Austin, Texas, United States of America

Role Detail

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

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

Compensation and Benefits

Compensation ranges vary depending on location and may include:

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

Post To

• External careers site
• Internal careers site