Applied AI Engineer

Design, develop, and deploy machine learning models for real-world use cases (player behavior prediction, personalization, retention modeling, fraud detection, etc.).

Build and maintain data pipelines (ETL/ELT) to collect, clean, and process large datasets from multiple sources (game analytics, APIs, user data).

Collaborate with product and engineering teams to integrate AI models into production environments (APIs, backend systems).

Implement and manage MLOps practices model versioning, CI/CD for ML, monitoring, and retraining pipelines.

Conduct exploratory data analysis (EDA) to uncover insights and guide model features.

Optimize models for accuracy, latency, and scalability.

Develop dashboards and reports to communicate model performance and insights to non-technical stakeholders.

Stay current with advances in ML/AI frameworks (LLMs, deep learning, reinforcement learning) and proactively propose innovative ideas.