Officience
AI Engineer (LLM Training & Fine-tuning)
- Compensation
- $900–$1.3K / mo
- Location
- Hồ Chí Minh, Vietnam
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 1+ years
- Category
- Ai engineering
- Posted
Skills
Nice to have
- Experience with AWS, Microsoft Azure, MLOps, and distributed training.
- Experience with Multimodal AI (VLM) and Document AI fine-tuning.
- Experience designing production-grade Agentic AI systems, including RAG, planning, memory, and multi-agent orchestration.
- Publications at CORE Rank A/A* conferences (e.g., ACL, EMNLP, NAACL) are a strong advantage; conference ranks should be checked against the relevant ranking edition.
- Ability to read, reproduce, and implement methods from AI research papers.
Full description
Top 3 Reasons To Join Us
Attractive offer with human-centric environment
Flexible work-from-home policy (90 days/ year)
Lunch served on the spot with diversified menu
The Job
We are looking for a skilled AI Engineer with a strong foundation in Machine Learning, Deep Learning, and NLP. The ideal candidate has hands-on experience in LLM fine-tuning, OCR & Document Understanding, and AI Agent/Multi-Agent systems, with the ability to develop, optimize, and deploy AI models in production. This role focuses on Core AI/ML Engineering, LLM Fine-tuning, and Agentic AI. Candidates are expected to have hands-on model training and fine-tuning experience, rather than solely LLM API integration, prompt engineering, or RAG chatbot development.
- Research, develop, train, fine-tune, and deploy AI/ML models.
- Fine-tune open-source LLMs using LoRA, QLoRA, PEFT, and SFT.
- Develop OCR, Document Understanding, and Information Extraction solutions.
- Design and implement AI Agent and Multi-Agent systems for complex workflows.
- Build and optimize model training, evaluation, and inference pipelines.
- Research and implement advanced AI techniques from academic papers.
Your Skills and Experience
- Education: Bachelor's degree/Master’s degree in Data Science, Artificial Intelligence, Computer Science, or a related field.
- Experience: Minimum 1–2 years of hands-on experience in AI/ML (industry experience)
- Programming: Python, TypeScript/JavaScript, SQL.
- ML Frameworks & Libraries: PyTorch, TensorFlow, NumPy, Pandas.
- AI/Deep Learning: Strong understanding of ML, DL, NLP, and Transformer architectures.
- LLM Fine-tuning: Hands-on experience with LoRA, QLoRA, PEFT, and SFT on models such as Qwen, Llama, and Mistral.
- AI Agents & Multi-Agent Systems: LangGraph, LangChain, CrewAI, or equivalent; tool calling, agent orchestration, multi-agent collaboration.
- Document AI: OCR, Document Layout Analysis, and Information Extraction.
- Model Optimization: GPU/CUDA, quantization, hyperparameter tuning, model evaluation.
- Deployment: FastAPI, RESTful APIs, vLLM, or equivalent frameworks.
- Database: PostgreSQL, MySQL.
- DevOps: Docker, Git (version control), Linux, CI/CD (GitHub Actions, GitLab CI).
Nice to have
- Experience with AWS, Microsoft Azure, MLOps, and distributed training.
- Experience with Multimodal AI (VLM) and Document AI fine-tuning.