Cardinal Health - Charleston, WV

posted about 1 month ago

Full-time - Mid Level
Charleston, WV
Merchant Wholesalers, Nondurable Goods

About the position

The Full Stack Machine Learning Engineer at Cardinal Health's AI CoE is responsible for developing, deploying, and integrating AI solutions that enhance healthcare operations and improve patient outcomes. This role combines expertise in machine learning, software engineering, and user interface development to create impactful AI-driven systems. The engineer will work with generative AI technologies, build machine learning models, develop APIs, and collaborate with business stakeholders to translate their needs into actionable solutions.

Responsibilities

  • Explore, implement, and support Generative AI solutions, including Large Language Models and Retrieval Augmented Generation systems.
  • Develop, deploy, and support machine learning models for various applications such as forecasting and risk prediction.
  • Build and maintain robust GenAI/ML pipelines ensuring data quality and model training efficiency.
  • Design, develop, and maintain RESTful APIs for integrating ML models and GenAI solutions with existing systems.
  • Collaborate with the team to design and develop user interfaces for applications leveraging ML models and GenAI solutions.
  • Work closely with business stakeholders to understand their needs and translate them into AI-driven solutions.
  • Stay updated on emerging technologies in AI, particularly in ML, GenAI, LLMs, and RAG technologies.

Requirements

  • Bachelor's degree in Computer Science or related field, or equivalent work experience.
  • 2-4 years of experience in a relevant field.
  • Strong understanding of machine learning algorithms and techniques.
  • Proficient in Python and familiar with machine learning libraries like Scikit-learn, TensorFlow, or PyTorch.
  • Experience with cloud platforms like GCP, AWS, or Azure for data processing and model management.
  • Familiarity with data engineering principles and data pipelines.
  • Experience with front-end technologies (HTML, CSS, JavaScript, potentially React) and backend technologies (Python, Node.js).
  • Excellent communication skills for collaboration with technical and non-technical stakeholders.
  • Experience with Generative AI, LLMs, and RAG technologies.
  • Familiarity with CI/CD pipelines for GenAI solutions and ML models.

Nice-to-haves

  • Experience working with healthcare data and understanding of HIPAA regulations.
  • Knowledge of software engineering patterns and best practices.
  • Experience with Agile development methodologies and DevSecOps principles.

Benefits

  • Medical, dental and vision coverage
  • Paid time off plan
  • Health savings account (HSA)
  • 401k savings plan
  • Access to wages before pay day with myFlexPay
  • Flexible spending accounts (FSAs)
  • Short- and long-term disability coverage
  • Work-Life resources
  • Paid parental leave
  • Healthy lifestyle programs
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