WILL is an entrepreneurial laboratory incubated by WizardQuant. Starting from but not limited to financial scenarios, WILL sincerely invites students, new graduates, and experienced professionals to join us and embark on a journey across vast expanse of artificial intelligence.

AI researchers focus on building the next generation of AI models and algorithms that will propel us towards ASI for Sci-Tech. The ideal candidates should have profound expertise in deep learning, reinforcement learning, and advanced reasoning models. You’ll conduct innovative research on LLMs and work with engineers to implement research outcomes at scale. We expect you to be hands-on, innovative, enthusiastic to solve real problems and eager for breakthroughs.

Core Responsibilities

• Core model development: Keep up with the forefront oftechnology, innovate model architecture, enhance model performance in various stages such as data synthesis, pre-training, and post-training, and improve reasoning and planning capabilities.
• Training method optimization: Optimize training algorithmsand paradigms, improve model efficiency and performance, and explore Scaling Law boundary.
• Evaluation & Benchmarking: Develop reliable evaluation metrics and benchmarks to measure model performance, inferencecapability, and security, enhance understanding of models, and help improve
• Cross-team collaboration: Work closely with AI engineers to transformresearch prototypes into scalable implementations. Guide the integration of new algorithms with AI infrastructure to solve engineering challenges in training, deployment, and inference.

Qualifications

• Outstandingresearch experience in deep learning, reinforcement learning and other relevant fields, familiar with NLP/LLM algorithms at all stages, ACM/ICPC/IOI winners are preferred.
• Excellent engineering ability, proficient in using frameworks such as PyTorch/TensorFlow/JAfor prototype development, familiar with data analysis and scientific computing related libraries.
• Excellent analytical skills and creative thinking, tackling problems with first principles thinking, formulating hypotheses and verifying them through experiments.
• Passionate about cutting-edge AI research, technology-driven, stronghands-on ability, able to transform theories into practical models.