We are exploring the next generation of AI-native systems, where large models evolve from passive assistants into autonomous agents capable of reasoning, planning, and interacting with complex environments.

Building on our expertise in edge AI, multimodal sensing, and large-scale model systems, we are developing agent architectures that integrate perception, tool use, and long-horizon task execution.

We are looking for an AI Engineer Intern to help design and build agent-based systems powered by large language models and multimodal models. You will work closely with researchers and engineers to prototype new agent workflows, evaluate emerging agent frameworks, and build practical systems that extend AI capabilities from conversation to action.

This position is ideal for students who are passionate about AI agents, large models, autonomous workflows, and AI-native development environments.

What you will be doing:

. Agent Architecture Development

Design and prototype AI agent architectures capable of reasoning, planning, and executing multi-step tasks.

. LLM-based Systems Engineering

Develop pipelines that integrate large language models with tools, APIs, and external environments.

. Tool Use & Automation
Build tool interfaces that allow agents to interact with software environments (e.g., code execution, web interaction, data processing).

. Agent Evaluation
Design experiments and benchmarks to evaluate agent capabilities, such as reasoning, coding, planning, and task completion.

. AI-native Workflows
Explore how agent systems can augment engineering workflows, including developer copilots, automated debugging, and task orchestration.

What you should have:

. Currently pursuing in Computer Science, Artificial Intelligence, or a related field

. Solid understanding of deep learning and large language models

. Familiarity with LLM application development, such as prompt engineering, tool calling, or retrieval systems

. Strong programming skills in Python

. Experience with PyTorch, TensorFlow, or similar deep learning frameworks

. Strong problem-solving skills and ability to work independently

. Good communication and documentation skills

Preferred Skills:

. Experience building AI agents or LLM-based applications

. Familiarity with agent frameworks (LangChain,Langraph,agno,openclaw,mem0,etc)

. Experience with multimodal models (vision-language models, document understanding)

. Experience with AI-assisted coding workflows

. Open-source contributions or research projects related to LLMs, agents, or AI systems

AI Engineer Intern (Agent) - Aug 2026 onwards (3/6 months)