Large Language Model Fine-tuning Engineer (Senior Level)

Job Responsibilities:

  • Responsible for fine-tuning large language models to improve their performance on specific tasks and able to innovate based on large models.
  • Design and implement fine-tuning algorithms, adjust hyperparameters, and optimize model performance.
  • Preprocess and analyze data during fine-tuning to ensure the quality and applicability of the dataset.
  • Evaluate and analyze fine-tuning results, and adjust the model to improve its performance.
  • Collaborate with team members and guide others to ensure the smooth progress of fine-tuning tasks and high-quality results.
  • In-depth understanding of the latest technologies and applications for large language models, and constantly improving fine-tuning skills and knowledge.

Job Requirements:

  • Master’s degree or above in computer science, artificial intelligence, mathematics or related fields, with relevant background knowledge in machine learning, deep learning, and natural language processing.
  • More than 5 years of working experience in NLP-related fields and more than 2 years of project management experience, with significant responsibilities in well-known AI companies and projects.
  • Familiar with mainstream LLMs and experience in tuning them are preferred.
  • Experience in practical application of human-in-the-loop reinforcement learning is preferred.
  • Familiar with deep learning frameworks (such as TensorFlow, PyTorch, etc.) and commonly used model evaluation and tuning, performance acceleration techniques, familiar with commonly used AI generation model frameworks, including GAN, VAE, VQGAN/Diffusion, etc.
  • Proficient in data processing and analysis skills, able to process and analyze large-scale text datasets.
  • Strong team collaboration and communication skills, able to work closely with other team members to complete fine-tuning tasks.
  • Ability to learn quickly and solve problems, continuously learning the latest technologies and solving practical problems.

Location: Shanghai, Singapore, or the United States

Please contact if you are interested in any of these openings, and we also welcome help from recruiting agencies.