Job description for AI Engineer at PT Code Development Indonesia
- 3+ years of hands-on experience in developing and deploying ML models into real-world business applications or research environments.
- Strong understanding of ML/DL frameworks such as Jupyter Notebook, Anaconda, TensorFlow, Keras, Scikit-learn, PyTorch, and MXNet.
- Proven experience working with cloud service platforms (AWS, Azure, or GCP) for ML/DL pipeline orchestration including GPU-based training (CUDA), model evaluation, and deployment (e.g., SageMaker, Docker, or Vertex AI).
- Proficiency in Python and core data/ML libraries such as Pandas, NumPy, and Scikit-learn.
- Solid grasp of machine learning algorithms (classification, regression, clustering, feature selection, hyperparameter tuning, etc.).
- Experience developing and fine-tuning Large Language Models (LLMs) for text, code, or image generation.
- Understanding of Retrieval-Augmented Generation (RAG) architecture, including knowledge of vector databases (e.g., FAISS, ChromaDB, Milvus) and embedding models.
- Experience integrating LLMs with external tools, APIs, and data sources through frameworks such as LangChain, LlamaIndex, or similar orchestration layers.
- Familiarity with MCP (Model Context Protocol) or modern context-sharing protocols for building scalable, composable AI systems.
- Experience implementing modern AI pipelines involving fine-tuning, prompt engineering, context retrieval, and model evaluation workflows.
- Knowledge of model optimization and monitoring (latency, throughput, token efficiency, and hallucination detection).
- Ability to collaborate with cross-functional teams (data engineers, analysts, and software developers) to deliver AI-powered features and applications
