NLP Research Intern
LIGHTSPEED STUDIOS is made up of passionate players who advance the art & science of game development through great stories, great gameplay, and advanced technology. We are focused on bringing next generation experiences to gamers who want to enjoy them anywhere, anytime, across multiple genres and devices.
Lightspeed Tech Center is a R&D department under Lightspeed Studios which develop PUBG Mobile and other high-quality games. Our Tech Center leads the research, exploration, and discovery of innovative technologies and provides technical services for all games during all phases of life cycle, including engine, audio, QA, AI, next generation game, technical cooperation, etc.
LightSpeed Studios is one of the world’s most innovative and successful game developers. With team across China, United States, Singapore, Canada, United Kingdom, France, Japan, South Korea, New Zealand, and United Arab Emirates. We are expanding to more countries.
Founded in 2008, LightSpeed Studios has created over 50 games across multiple platforms and genres for over 4 billion registered users. It is the co-developer of worldwide hits PUBG MOBILE, Apex Legends Mobile, and League of Legends: Wild Rift (Chinese Version).
- Drive and contribute to cutting-edge research projects in NLP/ML.
- Develop benchmarks and baselines using publicly available datasets.
- Train large language models (LLMs) on innovative, practical tasks.
- Publish research findings at leading NLP/ML/AI conferences and in top journals.
- Currently in the PhD degree in NLP, Machine Learning, or a related area, or recently submitted the thesis; available at least three days per week (with the supervisor and university approval). Candidates who have completed a Master's degree and have received a PhD offer in a relevant field will also be considered.
- At least one publication in a top-tier NLP/ML conference or journal (e.g., ACL, NAACL, EMNLP, EACL, NeurIPS, ICLR, ICML).
- Hands-on experience with Python and deep learning libraries, especially PyTorch, Hugging Face, and Transformers.
- Experience in one or more of the following areas: supervised fine-tuning of LLMs, LLM self-learning, LLM efficiency, LLM-based AI agents, or LLM applications in gaming, reasoning, or mathematical tasks.
