Principal AI Engineer

Job Overview
This role is a core member of Bybit’s AI team, covering both LLM Application Engineering and Personalized Recommendation Systems. You will participate in the algorithm development of Bybit’s flagship AI product TradeGPT, lead end-to-end optimization of the recommendation system, and directly drive platform user growth and trading experience improvement through algorithmic capabilities.

Responsibilities
1. LLM & AI Agent Direction

• Responsible for core AI algorithm development and iteration of Bybit’s AI Agent application TradeGPT

• Integrate mainstream AI platforms (OpenAI, Anthropic, Google Gemini, open-source models, etc.) and build a unified model access layer

• Build a Prompt Engineering framework to continuously improve model output quality and stability

• Design and implement a RAG knowledge base retrieval system to support accurate Q&A and decision assistance in financial scenarios

• Participate in AI product architecture design and technology selection, driving the team’s overall AI engineering capability growth

2. Recommendation System Direction

• Responsible for recommendation system algorithm development, covering the full pipeline of recall, ranking, and re-ranking

• Build user and asset profiles, mining user trading behavior and interest features

• Focus on cutting-edge directions (LLM + recommendation, sequential recommendation, multi-objective optimization) to drive technical implementation

• Design A/B testing experiments and continuously improve recommendation performance metrics through data-driven approaches

Requirements
Basic Qualifications

• 3+ years of software engineering experience, including 1+ year of AI/ML related project experience

• Strong Python skills, familiar with mainstream AI frameworks such as LangChain and LlamaIndex

• Hands-on experience with LLM API integration (OpenAI / Claude / Gemini, etc.)

• Understanding of RAG architecture and vector databases (Pinecone, Weaviate, Qdrant, etc.)

• Familiar with machine learning fundamentals (LR, GBDT, DNN), with complete experience in feature engineering and offline training + online serving

• Good engineering practices: code quality, unit testing, CI/CD standards

Preferred Qualifications

• Experience with model fine-tuning (Fine-tuning / LoRA / RLHF)

• Familiar with MLOps toolchains (MLflow, Weights & Biases, etc.)

• Experience in Agent / Multi-agent system development

• Experience with big data processing (Spark / Hive / Flink)

• Understanding of AI safety and Responsible AI practices

• Experience with cloud platform AI services (AWS / GCP / Azure)

• Previous algorithm experience in finance, cryptocurrency, or trading scenarios is a plus