Key Responsibilities

• High-Impact Publications: Publish research in top-tier conferences, file patents, and contribute to the open-source AI community through the release of datasets, models, and code.

• Original Research Breakthroughs: Explore cutting-edge AI research and industry trends to lead impactful, forward-looking research and achieve original break- throughs.

Basic Requirements

• Solid theoretical foundation in machine learning, deep learning, natural language pro- cessing (NLP), computer vision (CV), and reinforcement learning (RL).

• Strong programming skills, proficient in Python and C/C++ under Linux, capable of independently implementing complex deep learning models and system modules, with expertise in debugging and performance optimization.

• Familiarity with mainstream architectures, including language models (Transformers and variants, Linear Attention), multimodal models (LLaVA-like, native MLLMs), gener- ative models (Autoregressive, DiT), and reasoning models (o1 / PPO).

• Excellent problem-solving ability, strong teamwork mindset, and effective communi- cation skills.

Preferred Qualifications

• Familiarity with high-performance operator frameworks such as CUDA/Triton/Cutlass.

• Experience with distributed RL frameworks such as veRL / OpenRLHF / Ray.

• Knowledge of large-scale RL environment construction for browser / computer use / code sandbox tasks.

• Experience with distributed training frameworks such as Megatron-Core / Deep- Speed, including multi-node training efficiency tuning and optimization of computation‒communication overlap.

• Outstanding achievements in competitive programming (ACM/ICPC, NOI/IOI, Code- forces, TopCoder).

• Contributions to well-known open-source large model projects or winning results in related competitions.