AI/ML Engineer - Hybrid Onsite

UnitedHealth Group•Minnetonka, MN

1d•Hybrid

About The Position

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. This position follows a hybrid schedule with four in-office days per week.

Requirements

Undergraduate degree or equivalent experience
3+ years of proven experience working with Large Language Models (LLMs)
3+ years of experience with machine learning concepts and fine-tuning methodologies
3+ years of professional coding experience in Python, following PEP8 standards
Experience using the LangChain framework.
Experience with Retrieval-Augmented Generation (RAG) techniques
Experience with containerization technologies such as Docker
Experience ensuring production-quality code, including thorough testing and documentation
Experience with version control systems such as Git
Proven solid problem-solving skills and attention to detail
Proven ability to write clean, maintainable, and efficient code
Proven comfortable working in the terminal for development and deployment tasks

Nice To Haves

Healthcare experience
Statistical knowledge

Responsibilities

Develop and implement machine learning solutions using LLMs
Utilize the LangChain framework for working with closed source and open-source models
Apply fine-tuning methodologies to optimize machine learning models for specific tasks and datasets
Write clean, maintainable, and efficient code adhering to PEP8 standards
Utilize containerization technologies such as Docker for development and deployment
Ensure the production quality of code, including thorough testing and documentation
Be comfortable working on the terminal for various development and deployment tasks
Work on traditional machine learning methods like XGBoost for classification tasks and unsupervised learning techniques like K-means