Machine Learning Engineer
Role details
Job location
Tech stack
Job description
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., We support senior engineers with autonomy and opportunities to shape long-term technical direction.
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 Google Cloud Platform, 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.
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.
Benefits & conditions
- Washington (depending on location e.g. Seattle vs. Spokane) *$118,700 - $154,100 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.
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.
