• Contribute to the design and execution of experiments in reasoning model training, post-training alignment, test-time scaling, or systematic model evaluation — with a focus on applications in financial and crypto-native contexts
• Review and synthesize recent academic literature at NeurIPS, ICML, ICLR, and ACL — tracking developments in reasoning, alignment, and agentic AI to inform and sharpen ongoing research directions
• Implement model variants, training procedures including RLVR-based approaches, and evaluation protocols using PyTorch and the Hugging Face ecosystem
• Track and log experiments systematically using Weights & Biases or equivalent — maintaining reproducibility standards throughout
• Explore the intersection of LLM reasoning and crypto-native data: on-chain signals, market microstructure, multi-modal market intelligence — identifying research opportunities unique to Binance's position
• Collaborate with applied engineering teams to understand how research findings translate into production constraints in a zero-downtime, 24/7 trading environment