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About NetEase Games:

As a leading internet technology company based in China, NetEase, Inc. (NASDAQ: NTES and HKEX:9999, “NetEase”) provides premium online services centered around content creation. With extensive offerings across its expanding gaming ecosystem, the Company develops and operates some of China’s most popular and longest-running mobile and PC games. Powered by industry-leading in-house R&D capabilities in China and globally, NetEase creates superior gaming experiences, inspires players, and passionately delivers value for its thriving community worldwide. By infusing play with culture and education with technology, NetEase transforms gaming into a meaningful vehicle to build a more entertaining and enlightened world.

NetEase’s ESG initiatives are among the best in the global media and entertainment industry, earning it a distinction as one of the S&P Global Industry Movers and an “A” rating from MSCI. For more information, please visit: http://ir.netease.com/

Job Description:
As an AI Engineer, you will be responsible for the practical implementation of reinforcement learning, imitation learning, and evolutionary algorithms in gaming scenarios. You will participate in the entire process from data cleaning to modeling for solving real-world problems, while collaborating with team members to summarize experiences and continuously improve our solutions.

Responsibilities:

• Participate in the implementation of reinforcement learning, imitation learning, and evolutionary algorithms, including but not limited to AI agents and game balancing tests.
• Develop more powerful, diverse, and human-like AI bots for game products using reinforcement learning and imitation learning technologies.
• Contribute to the development of reinforcement learning training and deployment platforms

Requirements:

• Master’s degree or above in Computer Science, Machine Learning, or related fields.
• Proficient in Python and PyTorch; experience with large-scale reinforcement learning training is preferred.
• Practical experience in deploying AI bots and difficulty adjustment is a strong plus.
• Solid foundation in reinforcement learning and imitation learning algorithms with engineering deployment experience.
• Strong problem-solving skills with the ability to independently analyze and address data-related issues.
• Excellent communication skills, self-motivation, and a strong learning mindset to stay up-to-date with emerging technologies.