Machine Learning Engineer III

Locations

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

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

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).

• * 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

Post To

• External careers site
• Internal careers site