AI Researcher Intern

About the role

We are currently seeking candidates that are bilingual in Mandarin Chinese and English. The estimated pay-rate will be $30 per hour, depending on education level.

Responsibilities

• Harness Architecture Design & Implementation - Research and design Agent execution framework, providing standardized runtime environment for intelligent agents
• Harness Architecture Design & Implementation - Implement tool call orchestration mechanism, supporting unified abstraction for function calling, API integration, and external system interaction
• Harness Architecture Design & Implementation - Build execution sandbox environment to ensure safety and controllability of Agent operations
• Harness Architecture Design & Implementation - Design task decomposition and planning engine, supporting automatic breakdown of complex goals and execution path optimization
• Harness Architecture Design & Implementation - Implement execution state tracking and anomaly recovery mechanisms to ensure reliability of long-running tasks
• Memory System Architecture Development - Design hierarchical memory architecture, covering storage and retrieval mechanisms for working memory, short-term memory, and long-term memory
• Memory System Architecture Development - Research memory compression and summarization techniques, enabling efficient storage of massive interaction history while preserving key information
• Memory System Architecture Development - Build context-aware memory system, supporting multi-dimensional memory association based on time, task, and user
• Memory System Architecture Development - Develop memory retrieval augmentation mechanisms, achieving deep integration of RAG and Agent memory
• Memory System Architecture Development - Explore memory forgetting and update strategies, balancing memory capacity with information timeliness
• Multi-Agent Collaboration Architecture - Research multi-Agent system architecture, design communication protocols and collaboration mechanisms between Agents
• Multi-Agent Collaboration Architecture - Implement role specialization and task allocation algorithms, supporting orchestration of expert Agents, coordinator Agents, executor Agents, and other roles
• Multi-Agent Collaboration Architecture - Build consensus achievement and conflict resolution mechanisms to handle decision disagreements among multiple Agents
• Multi-Agent Collaboration Architecture - Design Agent social behavior norms, simulating communication, negotiation, and feedback patterns in human team collaboration
• Multi-Agent Collaboration Architecture - Explore emergent behavior and collective intelligence, researching self-organization and adaptive capabilities in multi-Agent systems
• General Architecture Capabilities - Design Agent evaluation and benchmarking system, establishing quantitative capability metrics
• General Architecture Capabilities - Build Agent behavior interpretability framework, supporting decision process tracing and attribution analysis
• General Architecture Capabilities - Research Agent safety alignment mechanisms to prevent risks such as unauthorized operations, harmful outputs, and goal drift
• General Architecture Capabilities - Track cutting-edge Agentic AI research and translate academic achievements into engineering practice

Requirements

• Basic Qualifications - Must be currently pursuing a Master's degree or PhD in an AI related discipline
• Programming & Engineering - Proficient in Python, familiar with asynchronous programming, concurrency control, and performance optimization
• Programming & Engineering - Familiar with mainstream LLM frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, etc.)
• Programming & Engineering - Experience in large-scale distributed system design and implementation
• Programming & Engineering - Familiar with containerization technologies such as Docker and Kubernetes
• AI Expertise - Deep understanding of Transformer architecture and large model principles
• AI Expertise - Familiar with Prompt Engineering, Function Calling, Tool Use, and related technologies
• AI Expertise - Experience in RAG system development, familiar with vector retrieval, text Embedding, re-ranking, and related techniques
• AI Expertise - Understanding of reinforcement learning fundamentals; experience with RLHF, DPO, and related methods is a plus
• Research Capabilities - Ability to conduct independent technical research, responsible for the entire process from problem definition to solution implementation
• Research Capabilities - Strong literature reading and summarization skills, able to quickly absorb cutting-edge research achievements
• Research Capabilities - Capability in technology selection and evaluation, able to make reasonable decisions among multiple solutions
• Soft Skills - Strong passion for AI technology, keeping up with the latest developments in the Agentic AI field
• Soft Skills - Excellent communication and collaboration skills, able to work efficiently with engineering teams
• Soft Skills - Critical thinking ability, capable of objectively evaluating and iteratively optimizing technical solutions

Benefits

• Medical, dental, and vision insurance
• 401(k) retirement plan with a company match that vests fully on day one
• Paid parental leave after just three (3) months of employment
• Paid time off policy that includes vacation time, personal time, sick time, floating holidays, and company holidays
• Flexible spending and health savings accounts
• Life and AD&D insurance
• Short- and long-term disability coverage
• Legal assistance
• Supplemental plans such as pet, critical illness, accident, and hospital indemnity insurance
• Commuter benefits
• Well-being initiatives
• Peer-to-peer recognition programs

Qualifications

• Must be currently pursuing a Master's degree or PhD in an AI related discipline
• Proficient in Python, familiar with asynchronous programming, concurrency control, and performance optimization
• Familiar with mainstream LLM frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, etc.)
• Experience in large-scale distributed system design and implementation
• Familiar with containerization technologies such as Docker and Kubernetes
• Deep understanding of Transformer architecture and large model principles
• Familiar with Prompt Engineering, Function Calling, Tool Use, and related technologies
• Experience in RAG system development, familiar with vector retrieval, text Embedding, re-ranking, and related techniques
• Understanding of reinforcement learning fundamentals; experience with RLHF, DPO, and related methods is a plus