AI Algorithm Intern (LLM & NLP)

About us

Established in March 2018, Bybit is one of the fastest growing cryptocurrency derivatives exchanges, with more than 70 million registered users. We provide innovative trading services, staking products, and API support to retail and institutional clients worldwide. Reliability, resilience, and transparency are at the core of our mission.

Role Overview

As an AI Algorithm Intern, you will join our AI team to focus on the research and development of Large Language Model (LLM) applications and foundational NLP tasks. You will assist in building simple AI Agents and Q&A systems, participating in the full lifecycle—from data processing to modeling and final application—within real-world business scenarios to enhance your engineering and algorithmic capabilities.

Key Responsibilities

• LLM Application Development: Participate in developing LLM-based applications, including Q&A systems, AI Agents, and algorithmic workflow systems.
• Workflow & Prompt Engineering: Assist in workflow development, prompt design, and optimization to improve model performance.
• Agent Interaction: Participate in the implementation of tool-calling (function calling) and basic multi-turn dialogue logic.
• Core NLP Tasks: Implement foundational NLP tasks such as text classification, information extraction (IE), and semantic matching.
• Small-Scale Modeling: Engage in the modeling and optimization of smaller-scale models (e.g., classification or sequence labeling tasks).
• Data Engineering: Perform data cleaning, basic feature processing, and analysis of experimental results.

Requirements

Basic Qualifications:

• Proficiency in Python: Strong coding habits and solid problem-solving skills.
• NLP Fundamentals: Mastery of common NLP tasks (text classification, NER, semantic matching, etc.) and their underlying methodologies.
• Modeling Experience: Fundamental experience in modeling, with the ability to independently train and tune simple classification or labeling models.
• Technical Knowledge: Deep understanding of Transformer and BERT architectures (including structure, training paradigms, and application scenarios).
• LLM Experience: Foundational experience using LLMs (e.g., calling LLM APIs, basic prompt engineering).
• Agent Awareness: Understanding of core AI Agent concepts (e.g., tool-use, multi-turn dialogue) or some basic hands-on practice.

Preferred Qualifications (Pluses):

• Practical experience in building Q&A systems or chatbots.
• Experience with LLMs (GPT, open-source models, etc.) and hands-on experience with Prompt Engineering or RAG (Retrieval-Augmented Generation).
• Familiarity with Machine Learning/Deep Learning basics (training pipelines, loss functions, etc.).
• Proficiency in Java or prior Java development experience is highly preferred.
• Background in Backend Development, including API design and implementation or involvement in full-cycle project deployments.
• Relevant course projects, personal projects, or contributions to open-source communities.