Research Data Scientist (AI)

TL;DR

Research Data Scientist (AI): Conduct original research in generative AI and LLMs applied to crypto-native problems with an accent on reasoning under uncertainty, agent reliability in adversarial financial environments, and multi-modal market intelligence. Focus on designing rigorous experiments, developing post-training methodologies, and applying test-time scaling techniques to improve agent performance in fast-moving markets.

Location: Work-from-home arrangement (may vary depending on the work nature of the business team)

Company

Leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users.

What you will do

• Conduct original research in generative AI and LLMs for crypto and financial domains, focusing on reasoning under market uncertainty, trading agent alignment, multi-agent coordination, and test-time scaling.
• Design and execute rigorous experiments, including hypotheses formulation, model variants with RLVR-based reasoning, ablations, and statistical analysis.
• Develop novel post-training methodologies and evaluation frameworks for LLMs in crypto contexts, assessing chain-of-thought quality, decision consistency, and robustness.
• Research and apply test-time scaling techniques like process reward models, self-consistency, and Monte Carlo Tree Search to enhance agent reasoning.
• Track developments in top ML conferences (NeurIPS, ICML, ICLR, ACL) and identify opportunities to apply state-of-the-art techniques to hirify.global challenges.
• Collaborate with engineers to bring research findings into production for real-world impact.

Requirements

• Bilingual English/Mandarin required to coordinate with overseas partners and stakeholders.
• Master's or PhD in Machine Learning, Computer Science, Mathematics, Statistics, or related field (exceptional Bachelor's with research output considered).
• 0–5 years of research or industry experience in ML/AI; academic lab or internship experience valued.
• Deep understanding of transformer architectures, LLM pretraining/post-training (RLHF to RLVR), and mathematical foundations (linear algebra, probability, etc.).
• Proficiency in Python and PyTorch; use AI-native development tools like Claude Code, Cursor, or Copilot Workspace.

Culture & Benefits

• Collaborate with world-class talent in a user-centric global organization with flat structure.
• Tackle unique, fast-paced projects with autonomy in an innovative environment.
• Results-driven workplace with career growth, continuous learning, competitive salary, and company benefits.
• Hands-on expertise via tailored training curriculum and 1:1 mentorship from industry leaders.