Electronic Arts - Machine Learning Operations Developer

1. Bachelor's degree in Computer Science, Data Science, or related field.
2. Experience as an MLOps Engineer or similar role in Machine Learning.
3. Understanding of cloud computing, data management, and machine learning algorithms.
4. Proficiency with programming languages such as Python, R, or Scala.
5. Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn).
6. Experience with infrastructure automation technologies like Docker, Kubernetes, Terraform, etc.
7. Must have an working knowledge of CI/CD principles and tools, including GitHub, GitLab, and Jenkins
8. Knowledge of data structures, data modeling, and software architecture.
9. Understanding of data analysis workflows and machine learning model lifecycle.
10. Comfortable working in an Agile environment.

We are a global team of creators, storytellers, technologists, experience originators, innovators and so much more. We believe amazing games and experiences start with teams as diverse as the players and communities we serve. At Electronic Arts, the only limit is your imagination.

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The Data & Analytics (DnA) function brings both quantitative and qualitative insights to the entire company (including all game teams) through Studio Analytics, Data Engineering, Data Science and Machine Learning Engineering. We develop our Studio's data technical capabilities to bring data insights right to the studio partners' fingertips.

EA serves millions of players with multi-genre online experiences via Live Services. Games of the last decade continue to entertain and engage audiences with new titles launching each year. The common need across all game experiences is modern personalization approaches that enhance and increase player experiences, using the latest Machine Learning technologies to retrofit and augment game features, game systems, and game mechanics. We are looking for a Machine Learning Operations (MLOps) who will work amidst unique technologies to deliver in-game Personalization by building global-scale production systems. You will report to the Lead of MLOps. If you have a passion for creating advanced analytics data products to allow partners to make crucial decisions, you want to make impacts to help player engagement by providing an autonomous platform; then we want to talk to you.

Responsibilities:

1. Collaborate with Machine Learning Engineers, Data Science, Data Architecture, Infrastructure, and Governance teams to design and implement machine learning systems.
2. Maintain scalable ML infrastructure across multiple regions.
3. Create ML pipelines for automating and accelerating ML deployment tasks.
4. Build end-to-end ML lifecycle management process, including data extraction and processing, model training and versioning, Hyper parameter tuning, evaluation, and deployment.
5. Implement robust software best practices, such as coding standards, code reviews, source control management, build processes, testing, and operations.
6. Monitor and improve the performance of machine learning models in production.
7. Contribute to the development of best practices for our MLOps strategies.
8. Stay updated on developments in MLOps technologies and frameworks.