Machine Learning Engineer III

Electronic Arts•Vancouver, BC

4d•$122,300 - $158,500•Hybrid

About The Position

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.

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. 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

Nice To Haves

Rust Experience a Plus

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.

Benefits

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
401(k)
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
retirement plan
bonus and other incentive programs
healthcare coverage
mental well-being support
retirement savings
paid time off
family leaves
complimentary games