UnitedHealthcare is looking to develop and deploy advanced artificial intelligence and machine learning solutions to support underwriting, actuarial, and operational teams, and to translate proof-of-concept models into scalable, production-ready software that complies with business objectives and responsible AI practices.
Requirements
- Proven experience deploying ML models into production environments
- Strong knowledge of MLOps tools and practices, including MLFlow, Docker, and CI/CD pipelines
- Solid understanding of statistics, probability theory, and machine learning algorithms
- Experience with enterprise AI platforms such as UAIS or similar systems
- Proficiency in Python and ML frameworks like TensorFlow and PyTorch
Responsibilities
- Translate proof-of-concept models into robust, scalable software using contemporary ML engineering practices
- Develop and maintain scalable data pipelines and model deployment frameworks utilizing tools such as MLFlow, Docker, and UAIS
- Apply advanced techniques including NLP, NLU, semantic understanding, intent classification, computer vision, deep learning, and ASR to address business challenges
- Leverage statistical modeling, optimization, and experimental design to improve model performance and reliability
- Ensure all AI solutions comply with internal governance standards and responsible AI practices
- Present analytical findings and model outcomes to leadership and cross-functional teams in a clear and actionable manner
- Maintain awareness of industry best practices and emerging trends in AI/ML to continuously improve solutions
Other
- 4+ years of experience in AI/ML engineering or data science with a focus on machine learning applications
- Excellent communication skills to present complex analytical concepts to diverse audiences
- Ability to collaborate effectively with cross-functional teams and stakeholders
- Flexible remote work arrangements
- Opportunities for professional development and career growth
