Machine Learning Engineer (AI/ML)
Core
Build cutting-edge recommendation systems for gaming content to personalize user experiences and drive engagement across gaming platforms.
Role type
Machine Learning Engineer (Recommendation Systems)
Builds
AI-driven content matching, user modeling strategies, and in-game image content distribution systems for gaming platforms.
Domain
Gaming industry, AI/ML, Recommendation Systems
Deliverable
production ML models
Required skills
Recommendation systems (retrieval, ranking, cold-start), Deep learning, Graph Neural Networks (GNNs), Collaborative filtering, Large-scale distributed data processing, User behavior analysis, Predictive modeling, LTV optimization
Preferred skills
Computer vision, Multimodal modeling, Reinforcement learning, Image content recommendation, Short-form video recommendation
Technologies
TensorFlow, PyTorch, Spark MLlib, Hadoop, Spark, Flink
Responsibilities
Design and optimize core recommendation models using collaborative filtering, deep learning, and GNNs; Develop AI-driven content matching and user modeling strategies for gaming scenarios; Implement user lifecycle value (LTV)-oriented recommendation strategies; Collaborate with Product, Data, and Operations teams to translate business requirements into AI/ML solutions; Support in-game image content distribution systems through algorithm optimization; Track and implement cutting-edge AI advancements like large-scale retrieval and multimodal learning.
Seniority
Mid-Senior, hands-on IC