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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.