AI Engineer LLM Training Fine-tuning

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.

• 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.
• 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.

• 13th month salary
• Bonuses on occasional events (VN national holidays, birthday, wedding, etc.)
• Lunch served right at pantry
• Monthly coffee allowance
• Club allowance
• Premium 24/7 healthcare package
• Annual healthcare check up at international clinic
• Training courses with diverse topics
• Innovative salary review process
• 12 leaves per year
• Laptop policy if any
• Flexible work-from-home policy (up to 90 days per year)
• Parking-free
• Onsite opportunities to France upon Client's request