Senior Machine Learning Engineer

EA - Electronic Arts

Stockholm, Sweden

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.

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.