AI Algorithm and Development Software Engineer

GE Healthcare GE Healthcare · Healthcare · Beijing, Beijing, China · Digital Technology / IT

AI Algorithm and Development Software Engineer at GE Healthcare responsible for fine-tuning LLMs, prompt engineering, function calling optimization, advanced reasoning technologies, building LLM evaluation systems, and developing core Agent runtime systems and multi-Agent collaboration mechanisms. The role involves translating research into implementable technical solutions for healthcare applications.

What you'd actually do

  1. Be responsible for the fine-tuning of large language models, including supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and domain-specific model adaptation, to improve model performance and adaptability in vertical scenarios.
  2. Conduct in-depth research and optimization on Prompt Engineering, design high-efficiency and high-robustness prompt templates, and explore advanced prompt strategies to enhance model output quality and task completion efficiency.
  3. Optimize the Function Calling capability of large models, improve the accuracy, stability and generalization of model tool invocation, and realize the seamless connection between models and external tools and services.
  4. Conduct research and implementation on advanced model reasoning technologies, including Chain of Thought (CoT), reflection mechanism, multi-step reasoning, and long context management, to solve complex reasoning tasks and extend the effective context window of models.
  5. Build a comprehensive LLM evaluation system, conduct all-round testing and evaluation on models, focusing on model hallucination problems, output stability, tool call accuracy, reasoning ability and other core indicators, and put forward targeted optimization plans.

Skills

Required

  • MS or PhD degree or above in Computer Science, Artificial Intelligence, Mathematics, Statistics or related majors
  • solid theoretical foundation in natural language processing, machine learning and deep learning
  • More than 3 years of relevant working experience in large language model algorithm research and development
  • familiar with the training, fine-tuning and inference process of mainstream open-source large models
  • Proficient in deep learning frameworks such as PyTorch, TensorFlow
  • familiar with model fine-tuning tools such as PEFT, LoRA
  • hands-on experience in large model parameter-efficient fine-tuning
  • In-depth understanding of Prompt Engineering, Function Calling, Chain of Thought and other LLM related technologies
  • practical project experience in model reasoning optimization and long context processing
  • Proficient in Python programming
  • good data structure and algorithm foundation
  • strong code implementation and problem-solving abilities
  • strong learning ability and innovative thinking
  • pay attention to industry cutting-edge dynamics
  • ability to independently tackle key technical problems
  • Good communication and collaboration skills
  • efficiently cooperate with cross-team members to promote project progress

Nice to have

  • CUDA/CuFFT/CuBLAS, OpenMP, SIMD vectorization
  • Experience with git, jenkens, devops, etc.
  • Publications/competitions or open-source contributions
  • Experience in building LLM evaluation systems and conducting model hallucination, stability and tool call accuracy testing

What the JD emphasized

  • fine-tuning of large language models
  • Prompt Engineering
  • Function Calling capability
  • model reasoning technologies
  • LLM evaluation system
  • Agent runtime system
  • multi-Agent collaboration mechanisms

Other signals

  • fine-tuning LLMs
  • prompt engineering
  • function calling
  • agent runtime system
  • multi-agent collaboration
  • LLM evaluation system