At UnitedHealthcare, the business problem is to simplify the health care experience, create healthier communities, and remove barriers to quality care by designing, developing, and deploying scalable AI/ML solutions that integrate seamlessly into existing business tools.
Requirements
- 4+ years of experience in AI/ML engineering or AI/ML data science
- Proven experience deploying ML models into production environments
- Experience with MLOps tools and practices (e.g., MLFlow, Docker, CI/CD)
- Solid understanding of statistics, probability theory, and machine learning algorithms
- Familiarity with enterprise AI platforms such as UAIS or similar
- Solid proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch)
- Experience in underwriting or actuarial domains, including risk scoring, pricing models, or claims analytics
Responsibilities
- Translate proof-of-concept models into robust, production-grade software using modern ML engineering practices
- Collaborate with business stakeholders to understand requirements and deliver AI/ML solutions that enhance decision-making and efficiency
- Present complex analytical concepts and model outcomes to leadership and cross-functional teams in a clear, actionable manner
- Apply advanced techniques including NLP, NLU, semantic understanding, intent classification, computer vision, deep learning, and ASR to solve business problems
- Build and maintain scalable data pipelines and model deployment frameworks using tools such as MLFlow, Docker, and UAIS
- Leverage statistical modeling, optimization, and experimental design to improve model performance and reliability
- Ensure compliance with internal governance standards and responsible AI practices
Other
- 4+ years of experience
- Bachelor's degree (not explicitly mentioned but implied)
- Work remotely from anywhere within the U.S.
- Adhere to UnitedHealth Group's Telecommuter Policy
- Pass a drug test before beginning employment
