- Design, fine-tune, and evaluate LLMs (e.g., GPT, Llama, Claude, Mistral) for specific enterprise or domain needs.
- Develop custom model architectures, embeddings, and prompt engineering strategies.
- Implement techniques for model compression, retrieval-augmented generation (RAG), and multi-agent orchestration.
- Build scalable pipelines for training, evaluation, and deployment of LLM-based applications.
- Integrate LLMs with APIs, databases, and enterprise software systems.
- Work closely with Data Engineers, ML Engineers, and Product teams to translate business problems into AI solutions.
Experiment with new methods for grounding, alignment, and interpretability.
Minimum Qualifications: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related field.
- Strong proficiency in Python and frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, Llama Index, and LangChain.
- Deep understanding of LLM architectures, tokenization, embeddings, attention mechanisms, and finetuning strategies.
- Experience with vector databases (e.g., Pinecone, Milvus, FAISS) and RAG pipelines.
- Solid experience with cloud-based AI services (AWS SageMaker, Azure OpenAI, GCP Vertex AI, etc.).
- Strong background in NLP, information retrieval, and knowledge graph integration is a plus.
CODE.ID was previously a business unit of INTEGRASI, a system integrator that also provided software services established in 1999. In 2014, CODE.ID becomes an independently run company which currently has around 100 passionate developers with a myriad numbers of skill sets. CODE.ID has been established since 1999 and became a publicly listed company in Jakarta Stock Exchange in as PT Integrasi Teknologi Tbk. It was back to be a private company in 2007. Our Success Stories: We successfully developed, deployed, and supported Information Technology Infrastructure for Komisi Pemilihan Umum (KPU) or the National Election Commission in 2004. We developed the election application and also distributed, installed, and supported (7x24 hour) two data centers and 8000 VPN connected personal computers in 5,000 locations in the cities, rural areas, and remote areas all over Indonesia.