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Electronic Arts

Machine Learning Engineer III

Vancouver, BC, Canada

Posting language: English
Posted: Oct 1, 2026

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Applications open in a new tab.

Original job description

General Information

Locations: Kirkland, Washington, United States of America

Location: Kirkland
State: Washington
Country: United States of America

Location: Vancouver
State: British Columbia
Country: Canada

Location: Austin
State: Texas
Country: United States of America

Role ID

212201

Worker Type

Regular Employee

Studio/Department

CT - Security

Work Model

Hybrid

Description & Requirements

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

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 other incentive programs.

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 other incentive programs.

About Electronic Arts

We’re proud to have an extensive portfolio of games and experiences, locations around the world, and opportunities across EA. We value adaptability, resilience, creativity, and curiosity. From leadership that brings out your potential, to creating space for learning and experimenting, we empower you to do great work and pursue opportunities for growth.

We adopt a holistic approach to our benefits programs, emphasizing physical, emotional, financial, career, and community wellness to support a balanced life. Our packages are tailored to meet local needs and may include healthcare coverage, mental well-being support, retirement savings, paid time off, family leaves, complimentary games, and more. We nurture environments where our teams can always bring their best to what they do.

Electronic Arts is an equal opportunity employer. All employment decisions are made without regard to race, color, national origin, ancestry, sex, gender, gender identity or expression, sexual orientation, age, genetic information, religion, disability, medical condition, pregnancy, marital status, family status, veteran status, or any other characteristic protected by law. We will also consider employment qualified applicants with criminal records in accordance with applicable law. EA also makes workplace accommodations for qualified individuals with disabilities as required by applicable law.

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More about this job

Responsibilities

Design, build, and maintain scalable data ingestion and machine learning pipelines to support fraud and anti-cheat systems. Partner with data scientists to productionize models while ensuring data consistency, quality, and reliable infrastructure.

Requirements

Requires five or more years of professional experience in data or machine learning engineering with production ownership. Strong proficiency in Python, SQL, and experience with cloud environments, containerization, and orchestration tools is essential.

Skills

Python
SQL
Rust
Data engineering
Machine learning engineering
Cloud computing
AWS
GCP
Docker
Kubernetes
CI/CD
GitLab
Terraform
Spark
Fraud detection
Anti-cheat systems

Benefits

Paid time off
Sick time
Paid company holidays
Paid parental leave
Medical insurance
Dental insurance
Vision insurance
Life insurance
Disability insurance
401(k)
Retirement plan
Mental well-being support

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Data Engineering
Python
SQL
Rust
AWS
GCP
Docker
Kubernetes
CI/CD
GitLab
Terraform
Spark
Fraud Detection
Anti-cheat
Data Pipelines
Feature Engineering
Model Deployment
Cloud Infrastructure
Security
Data Labs
Production-grade
Scalability
Orchestration
System Integrity
Live Services
Infrastructure
Data Science
Back-end
Software Engineering

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