Game AI Researcher

3 days ago

Singapore NETEASE INTERACTIVE ENTERTAINMENT PTE. LTD. Full time $90,000 - $120,000 per year
Job Responsibilities:

Research and Development:
  • Responsible for the research and development of Agent technologies based on Large Language Models (LLMs) and Vision-Language Models (VLMs) in open-world game scenarios, covering key technologies such as Prompt Engineering, In-Context Learning (ICL), Retrieval-Augmented Generation (RAG), Supervised Fine-Tuning (SFT) and Reinforcement Fine-Tuning (RFT).
Framework and Toolchain Construction:
  • Lead the design and implementation of the core framework for game agents and promote the research and development of training data synthesis, automated evaluation systems and related algorithms.
Production Implementation:
  • Drive the deployment and integration of game agent technologies into both game content production and player-facing features, translating technical breakthroughs into practical applications.
Job Requirements:

Educational Background and Experience:
  • Master's degree or above in Computer Science, Artificial Intelligence or a related field.
  • At least 2 years of work experience in related fields (priority given to those with experience in AI, game AI, large models or agent technologies).
  • Or outstanding recent PhD graduates (priority given to those with matching research directions).
Theoretical Foundation and Research Capability:
  • Deep understanding of the principles of machine learning, reinforcement learning, deep learning and their applications in the internet/game industry.
  • Strong interest in cutting-edge AI technologies and solid research capabilities.
Large Model and Data Engineering:
  • Familiar with the basic principles, training paradigms and applications of leading large language models in the industry (e.g., Qwen, Deepseek, Claude, Gemini series, etc.).
  • Understanding of large model training data construction methodologies and proficiency in using relevant tools for data cleaning, preprocessing and formatting.
Technical Competency and Practical Experience:
  • Solid knowledge of core algorithms and technologies in related fields such as Reinforcement Learning (RL), Natural Language Processing (NLP) and Computer Vision (CV).
  • Proficiency in at least one programming language: C/C++, Go, or Python.
  • Skilled in mainstream deep learning frameworks such as TensorFlow and PyTorch, with engineering capabilities in model building, algorithm implementation and tuning.
  • Excellent hands-on skills, fast learning ability and logical thinking skills.
Good communication, expression and teamwork skills.

Strong interest and enthusiasm for the research and practical application of game AI technologies.

Mandarin speaking is required to liaise with peers and stakeholders in China.

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