Electronic Arts

The Office of the CXO drives effectiveness across the EA Experiences organization with a in business operations, comprehensive fan intelligence, plus internal technology and business solutions. We are horizontal connectors empowering teams across the Experiences organization with the strategic prioritization, investments, resources, data, insights, and technology required to accelerate business results in service of our goals.

And we want you to join us. We are hiring a Senior Machine Learning Engineer for our CXO Data & Analytics team, reporting to the Senior Manager of Data Science. This is an individual contributor role with no managerial responsibilities.

Responsibilities:

• Collaborate with a team of data scientists to transform concepts into production-ready ML/AI services.
• Work with cloud services such as AWS SageMaker for ML/AI model deployment for batch or real-time inference.
• Test, monitor, and optimize model performance in production environments. Set up CI/CD pipelines for automatic model updates and rollbacks.
• Ensure the reproducibility of models in production and use tools like Docker, Airflow and MLflow.
• Build relationships with IT, Data Engineering and other partners for successful transition from concept to production in a secure environment.
• Communicate requirements for product delivery and train data scientists to understand and complete the production process.
• Implement best coding practices (unit testing, version control) to ensure high-quality deliverables in production.

Qualifications:

• 5 or more years of experience in Machine Learning.
• Master's in a quantitative field such as Physics, Engineering, Statistics, or Mathematics (we will consider a Bachelor's degree with relevant experience)
• Experience applying data science, ML, and Deep Learning in a business context with a quantifiable impact.

Technical skills:

• Proficiency in writing clean and professional code in Python. Knowledge of libraries such as PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy. Knowledge of SQL.
• Experience deploying models into production: REST, FastAPI, Flask
• Containerization with Docker and Kubernetes
• Knowledge of MLOps and ML pipeline automation using Airflow or MLflow. Setting up CI/CD for ML model retraining and redeployment.

Soft skills:

• Customer-Centric – You put the customer/player at the center when designing new offerings and processes.  You understand how decisions and work affect player experience.
• Learner – Stay informed about relevant technology trends and developments with a growth mindset. You're not just open to learning new skills; you dive right in! 
• Experience creating detailed technical documentation and communicating complex topics to audiences with varying degrees of ML knowledge