Responsibilities:

• Design, train, fine-tune, and deploy large-scale ML models based on extensive healthcare data.
• Monitor and enhance model performance in production environments using the modern MLOps frameworks and tools.
• Collaborate with data scientists and medical experts to optimize model accuracy and efficiency, and advance product values.
• Work closely with data engineers to build systematic and automatic processes for model training, validation, and deployment.

• Qualifications:
  • Proficiency in Python and ML frameworks (Tensorflow, PyTorch, Lightning, etc.).
  • Solid knowledge of deep learning models and algorithms.
  • Basic understanding of MLOps and ML lifecycle.
  • Excellent problem-solving skills, attention to detail, and the ability to work both independently and collaboratively.
•  Preferred:
  • Experience with cloud platforms such as AWS, Azure, GCP, etc.
  • Experience with productization of ML softwares.
  • Experience with MLOps tools and processes.
  • Experience with Git and Github for version control and collaboration.
  • Experience with Docker and Docker Compose for software containerization and orchestration.
  • Experience with medical or healthcare data.
  • Publication records or academic achievements in AI-related fields.