Electronic Arts

The Engine Tech Quality team is seeking a Machine Learning Engineer to join our technical quality team. In this role, you will be responsible for developing and deploying data-driven solutions using existing and emergent tools and technologies to analyze large datasets and drive actionable improvements in our high-performance game engine code. 

You will work closely with cross-functional teams to help analyze and optimize, drive understanding and improve workflows across performance profiling, runtime memory management, and input latency measurements. 

Your work will have a strong impact on the players experience across multiple projects and activities within the Battlefield franchise. 

 Responsibilities 

• Translate research outcomes into production-ready solutions and products, and take ownership of their long-term development, support, and continuous improvement.
• Collaborate with engineers, technical artists, technical scripters and other team members to build and deploy scalable tools and workflows.
• Design, develop, and maintain robust data pipelines and ETL processes for large-scale processing of performance profiling, memory management, latency measurement data and other technical quality areas.
• Apply advanced analytics and statistical techniques to extract insights from complex datasets related to game engine performance.
• Implement and optimize algorithms for predictive modeling, anomaly detection, and automation of technical quality metrics.
• Stay up to date with the latest advancements in machine learning, big data, and generative AI, and proactively apply new techniques to solve technical quality challenges in game development.
• Document technical designs, processes, and results to facilitate knowledge sharing and reproducibility.

Requirements  

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.
• Solid understanding of statistical and quantitative data analysis.
• Solid understanding of machine learning concepts, algorithms, and best practices.
• Strong analytical and problem-solving skills, especially in the context of technical quality data.
• Proficiency in programming languages such as Python, C++, Java, or Scala.

Skills and Experience 

• Experience working with big data technologies such as Hadoop, Spark, or distributed databases.
• Experience with traditional Machine Learning framework such as Scikit-learn, PyTorch, TensorFlow, etc.

• Experience with data analysis and manipulation tools such as Pandas, Polars, Koalas, etc.

• Experience creating effective data visualizations to communicate complex technical insights.

• Experience with tools like Tableau, Grafana, PowerBI, Streamlit, etc.

• Experience with cloud platforms (AWS, GCP, or Azure) is a plus.
• Hands-on experience with MLOps practices for model management, deployment, monitoring, and tracking.
• Knowledge of data engineering principles and experience with large-scale data processing.
• Experience working with technical quality data such as performance profiling, runtime memory management, and input latency measurements in high-performance game engine code.
• Ability to work collaboratively in a team environment and communicate technical concepts to non-technical stakeholders.
• Self-driven with a strong sense of ownership and attention to detail.
• Excellent written and verbal communication skills.

Additional Information 

• Passion for working with technical quality data and creating impactful solutions for game engine performance.
• Interest in continuous learning and professional development in the fields of machine learning, AI, and game technology.