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Machine Learning Infrastructure Engineer Jobs in Seattle, WA

Machine Learning Engineer III

Kirkland, WA ยท On-site

$122K - $158K/yr

Together, we power the platforms, AI-driven tools, live services, and infrastructure that ensure ... The Senior Machine Learning Engineer will report to the Senior Manager, EA Player Security Data ...

This team builds core machine learning infrastructure and services. * Through close collaboration with product and engineering teams, we seamlessly integrate advanced intelligence into everyday user ...

This team builds core machine learning infrastructure and services. * Through close collaboration with product and engineering teams, we seamlessly integrate advanced intelligence into everyday user ...

Machine Learning Engineer

Seattle, WA ยท On-site

$120K - $140K/yr

The role We're adding an Machine Learning Engineer to our team to help us build and scale our core ... infrastructure and offline data cleanliness. As a result, we think Grid is positioned for efficient ...

The role We're adding an Machine Learning Engineer to our team to help us build and scale our core ... infrastructure and offline data cleanliness. As a result, we think Grid is positioned for efficient ...

Machine Learning Engineer

Seattle, WA ยท On-site

$120K - $140K/yr

The role We're adding an Machine Learning Engineer to our team to help us build and scale our core ... infrastructure and offline data cleanliness. As a result, we think Grid is positioned for efficient ...

Software Engineer, Systems ML

Bellevue, WA

$195K - $231K/yr

Meta is seeking a Software Engineer to join our Systems ML Engineering team, focused on building and optimizing the machine learning infrastructure that.

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Machine Learning Infrastructure Engineer information

See Seattle, WA salary details

$52.9K

$144.6K

$207.1K

How much do machine learning infrastructure engineer jobs pay per year?

As of Sep 14, 2026, the average yearly pay for machine learning infrastructure engineer in Seattle, WA is $144,605.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,300.00 and $160,500.00 per year, depending on experience, location, and employer.

What is a machine learning infrastructure engineer?

A Machine Learning Infrastructure Engineer designs, builds, and maintains the systems that support the development and deployment of machine learning models. This includes managing data pipelines, optimizing model training and inference, and ensuring scalability and reliability in production environments. They work closely with data scientists, ML engineers, and DevOps teams to create efficient workflows and infrastructure. Key technologies often include cloud platforms, containerization, orchestration tools, and distributed computing frameworks.

What are the key skills and qualifications needed to thrive as a machine learning infrastructure engineer?

To thrive as a Machine Learning Infrastructure Engineer, you need a strong background in computer science, cloud computing, distributed systems, and experience with machine learning frameworks, often supported by a degree in a related field. Familiarity with tools such as Docker, Kubernetes, Terraform, as well as cloud platforms like AWS, GCP, or Azure, and certifications in cloud or DevOps technologies are highly valued. Strong problem-solving abilities, effective communication, and collaboration skills help engineers work seamlessly with data scientists and cross-functional teams. These skills are essential to design, implement, and maintain robust, scalable infrastructure that enables efficient machine learning development and deployment.

What are some common challenges faced by machine learning infrastructure engineers, and how can these be addressed on the job?

Machine Learning Infrastructure Engineers often face challenges such as ensuring infrastructure scalability, managing resource allocation, and maintaining system reliability while supporting rapid experimentation by data science teams. Balancing the needs for flexibility in research environments with production-grade stability requires a deep understanding of both engineering best practices and the unique requirements of machine learning workflows. Collaboration with data scientists, clear communication about infrastructure capabilities, and staying current with fast-evolving technologies are key strategies for success. Most companies encourage ongoing learning and provide opportunities to contribute to architecture decisions, which makes this a rewarding environment for problem-solvers and innovators.

What are popular job titles related to Machine Learning Infrastructure Engineer jobs in Seattle, WA?

For Machine Learning Infrastructure Engineer jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Infrastructure Engineer jobs in Seattle, WA look for?

The top searched job categories for Machine Learning Infrastructure Engineer jobs in Seattle, WA are:

Infographic showing various Machine Learning Infrastructure Engineer job openings in Seattle, WA as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 75% Full Time, 20% Part Time, and 3% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $144,605 per year, or $69.5 per hour.

Machine Learning Engineer III

Kirkland, WA โ€ข On-site

Electronic Arts
PC Gamesย โ€ขย 10K+ employees

$122K - $158K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 25 days ago


Key responsibilities

  • Design, build, and maintain scalable data ingestion, transformation, and feature pipelines for machine learning workflows related to fraud and anti-cheat systems.

  • Own and operate production data and machine learning infrastructure, including data processing, feature generation, training workflows, and inference pipelines.

  • Partner with data scientists to productionize machine learning models, ensuring data consistency, quality, and reliable feature computation.


Job description

Locations

Kirkland, Washington, United States of America

  • Kirkland
  • Washington
  • United States of America
  • Vancouver
  • British Columbia
  • Canada
  • Austin
  • Texas
  • 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. Weโ€™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
  • * 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

Weโ€™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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