Research Scientist - LLM Foundation Models

Blockchain Academics; Hong Kong; Remote; HKD 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Remote-first work environment

Competitive salary

Career growth and learning

Job summary

Binance is seeking a highly skilled Research Scientist/Engineer to advance reasoning and planning in large foundation models. You will drive development across data acquisition, supervised fine-tuning, reward modeling, and RL, while designing robust evaluation methods.

You will enable models to interact with tools, APIs and code interpreters, and build agents and multi-agent systems for complex real-world challenges.

Qualifications

• Proficiency in RL, LLM and familiarity with large-scale model training.
• Strong data structures and fundamental algorithm skills; fluent in Python or C++/Java.
• Experience with influential projects or papers in RL, NLP or Deep Learning.

Responsibilities

• Reasoning and planning for foundation models across data acquisition, model evaluation, SFT, reward modeling, and RL.
• Synthesize large-scale, high-quality data via rewriting, augmentation and generation for pretraining, SFT, RL stages.
• Solve complex tasks using system 2 thinking and advanced decoding strategies like MCTS and A*.
• Develop robust evaluation methodologies to assess model performance at various stages.
• Teach models to use tools, interact with APIs and code interpreters; build agents and multi-agent systems.

Skills

RL & LLM

Large-scale model training

Python / C++ / Java

Data structures & algorithms

Research publications (RL/NLP/DL)

Job description

About the Role

We are seeking a highly skilled Research Scientist/Engineer to advance the reasoning and planning capabilities of large foundation models. In this role, you will enhance model performance across the entire development lifecycle—including data acquisition, supervised fine-tuning (SFT), reward modelling, and reinforcement learning—while driving innovations in reasoning and decision‑making. You will synthesise large-scale, high-quality datasets through rewriting, augmentation, and generation techniques to strengthen foundation models during pretraining, SFT, and RL stages. A key part of the role involves solving complex tasks using System 2 thinking and applying advanced decoding strategies such as MCTS and A*. You will design and implement robust evaluation methodologies, teach models to interact with external tools, APIs, and code interpreters, and build agents and multi‑agent systems capable of addressing sophisticated real‑world problems.

Responsibilities

• Reasoning and planning for foundation models: Enhance reasoning and planning throughout the entire development process, including data acquisition, model evaluation, SFT, reward modeling, and reinforcement learning, to improve overall performance.
• Synthesize large-scale, high-quality data using methods such as rewriting, augmentation, and generation to improve the capabilities of foundation models in various stages (pretraining, SFT, RL).
• Solve complex tasks using system 2 thinking and leverage advanced decoding strategies such as MCTS, A*.
• Investigate and implement robust evaluation methodologies to assess model performance at various stages.
• Teach foundation models to use tools, interact with APIs, and code interpreters. Build agents and multi-agent systems to solve complex tasks.

Requirements

• Proficiency in research experience with RL, LLM, and familiarity with large-scale model training is preferred.
• Proficiency in data structures and fundamental algorithm skills, and fluency in Python or C++/Java.
• Experience with influential projects or papers in RL, NLP, or Deep Learning is preferred.
• Excellent problem analysis and problem‑solving skills, capable of deeply addressing challenges in large-scale model training and application.
• Good communication and collaboration skills, with the ability to explore new technologies with the team and promote technological progress.

Why Binance

• Shape the future of finance
• Collaborate with world‑class talent in a user‑centric global organization with a flat structure
• Tackle challenging projects in a fast‑paced and innovative enviornment with autonomy
• Thrive in a results‑driven workplace with opportunities for career growth and continuous learning
• Competitive salary and company benefits
• Remote-first, work-from-home arrangement (may vary depending on the nature of the role and team)

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