Junior AI Application Developer (EN)
Department:
CSP (EN)
Form of Employment:
Official
Job Description
We are looking for a hands-on Junior AI Developer to join our team in building next-generation AI solutions. This role goes beyond simply running models on Google Colab — you will be directly involved in the end-to-end development lifecycle, from frontend interface development, backend logic implementation, and model optimization (RAG/Inference) to deployment packaging (Docker/Linux).
- AI Implementation: Deploy and optimize open-source LLMs (such as Llama 3, Qwen, Mistral, etc.) using Ollama or vLLM on on-premise infrastructure.
- System Development: Build RAG (Retrieval-Augmented Generation) systems integrated with Vector Databases such as ChromaDB, Milvus, and Qdrant.
- Fullstack Lite: Develop user interfaces (Web UI) using HTML5, CSS3, JavaScript (or React/Streamlit) and integrate them with Python APIs built on FastAPI/Flask.
- Deployment: Package applications into Docker containers, and manage as well as operate systems in Linux/Ubuntu Server environments.
- Open-source Contribution: Research, apply, and customize the latest open-source tools and frameworks from the global AI community.
Job requirements
Professional requirements:
Programming & AI Skills:
- Python: Strong proficiency in core Python, data processing, and API development.
- AI Tools: Hands-on experience with LangChain or LlamaIndex. Solid understanding of Prompt Engineering.
- Vector DB: Good understanding of embeddings and querying unstructured data.
Frontend & User Experience:
- Frontend: Strong knowledge of HTML5, CSS3, and JavaScript (ES6+). Familiarity with Tailwind CSS is an advantage.
- UI/UX: Basic aesthetic sense with the ability to design user-friendly and intuitive chatbot/dashboard interfaces.
Systems & Infrastructure:
- OS: Proficient in using Linux command line tools (Bash scripting), with understanding of process management and permission control on Ubuntu/CentOS.
- Docker: Ability to write Dockerfiles and use Docker Compose to set up AI runtime environments, including application containers, databases, and inference engines.
- Open-source: Habit of reading technical documentation on GitHub and capable of troubleshooting installation issues related to open-source libraries.
Additional requirements:
- Experience in building a home lab or deploying AI solutions on personal machines/private servers.
- Having real-world projects on GitHub (please attach the GitHub link in your CV).
- Good English reading comprehension for technical documentation.
Benefits:
- Competitive salary package, including base salary and performance bonuses.
- Probation period salary is 100% of the official salary.
- Comprehensive health and accident insurance.
- 15 days of annual leave, with 3 remote work days per month.
- Provision of work equipment (MacBook/Laptop, mouse, monitor, etc.).
- A creative and modern working environment.