Algorithm Engineer (LLM Systems)

Build Domain AI for the Future of Crypto

About Gate

Gate is one of the world's leading cryptocurrency exchanges, serving millions of users globally and ranking among the top exchanges by trading volume.

We believe the next generation of crypto platforms will be AI-native. Instead of simply integrating AI features, we are building systems where large language models, AI agents, and intelligent automation become core platform capabilities.

Our goal is to create domain-specialized AI systems for finance and crypto, enabling users to access information, insights, and decision-making tools in entirely new ways.

If you are excited about building real AI systems used by millions, we would love to talk.

The Role

We are looking for engineers who enjoy building and shaping domain AI systems.

You will work on training, fine-tuning, and optimizing large language models, and turning them into practical AI capabilities across the platform.

This includes building systems such as:

• Domain-specific AI assistants
• AI knowledge and Q&A systems
• AI copilots for financial insights
• AI agent capabilities powered by large models

You will collaborate closely with product and engineering teams to turn AI capabilities into real product systems.

What You'll Work On

• Train, fine-tune, and optimize large language models
• Design and implement model distillation pipelines to improve efficiency
• Build domain AI systems such as assistants, copilots, and Q&A tools
• Develop RAG architectures to integrate knowledge with LLMs
• Optimize models for real production environments
• Help shape how AI is integrated into a global crypto platform

Who You Are

You might be a great fit if you come from one of these backgrounds:

LLM Training / Model Systems

• Experience training or fine-tuning large language models
• Familiar with SFT, RLHF, model distillation, or model optimization
• Experience building domain-specific AI models

Applied AI / AI Systems

• Built AI assistants, AI copilots, or intelligent Q&A systems
• Experience with RAG, knowledge systems, or AI agents
• Experience building AI-powered products in real applications

We care most about engineers who build systems that work in production.

Requirements

• Strong background in Computer Science, AI, or Machine Learning
• Hands-on experience developing LLM or deep learning systems
• Strong experience with Python
• Familiarity with PyTorch, Transformers, or similar frameworks
• Strong engineering fundamentals and problem-solving ability
• Fluency in both Mandarin and English is required, as this role involves collaboration with engineering teams in China.

Nice to Have

• Experience in finance, trading, quant, or Web3 applications
• Experience building AI agents or complex AI systems
• Experience with model distillation or inference optimization
• Experience deploying AI systems at scale

Why Join

• Build domain AI systems for a global crypto platform
• Work on real-world AI problems at scale
• Collaborate with a global engineering team
• Fully remote worldwide, with collaboration primarily during APAC hours (Beijing / GMT+8).
• Competitive compensation

If you are excited about building domain AI systems that power the future of finance, we would love to hear from you.