AI Trainer - AI / ML & LLM Engineer (Remote, Freelance)

[About the Role]
We are looking for talented AI/ML engineers to help build, evaluate, and optimize next-generation AI systems. In this role, you will design and improve machine learning pipelines, fine-tune large language models, develop generative AI applications, and contribute to the research and engineering workflows that power real-world AI deployments.

This is a highly technical role ideal for engineers who enjoy solving complex ML problems, working with modern AI architectures, and pushing the boundaries of model performance and capability.

[What You’ll Do]
As an AI/ML & LLM Engineer, you will:
• Build, train, and optimize machine learning models, including LLMs and multimodal models.
• Develop and maintain ML pipelines, including data preprocessing, training, inference, monitoring, and performance optimization.
• Fine-tune LLMs for downstream tasks and design evaluation strategies to measure progress.
• Implement RAG (Retrieval-Augmented Generation) systems using vector databases and orchestration frameworks.
• Collaborate with cross-functional teams to design user-facing AI features and integrate models into production workflows.
• Conduct research explorations, benchmark different architectures, and experiment with new methods from recent papers.
• Build and deploy scalable ML services using Python-based frameworks, cloud platforms, and containerization tools.
• Document engineering decisions, model behavior, experiments, and results clearly.

[Requirements]
• Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, AI, Engineering, or a related field.
• Strong hands-on experience training, fine-tuning, or deploying ML models (2+ years preferred).
• Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX.
• Deep understanding of LLM internals: attention mechanisms, transformer architectures, embeddings, tokenization, and evaluation.
• Knowledge of RAG pipelines, vector databases, and prompt engineering.
• Experience with cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes).
• Strong analytical, debugging, and problem-solving skills.

• Native or professional proficiency in Traditional Chinese (TW).
• Excellent English communication and documentation skills.

[Preferred Requirements] 
• Experience contributing to ML research or implementing techniques from academic papers.
• Familiarity with MLOps pipelines, CI/CD for ML, model monitoring, and scalable inference systems.
• Prior work on agent-based systems, multimodal models, or distributed model training.
• Experience with LangChain, LlamaIndex, HuggingFace, or similar tools.
• Experience in RLHF, SFT, or developing datasets for LLM training.

Once we review your CV and determine that you may be a good fit for the role, we will contact you by email and provide further details about the interview process.