Key skills
AI/ML systemsSearch AIRanking AIGenerative AIAI feature developmentModel implementationAI development lifecyclePyTorchTensorFlowPre-trained modelsHugging FaceDatabricksAWS BedrockAzure MLAIMLAWSAzureBedrockPrototypingCollaboration
About this role
R1 RCM is a company focused on evolving the healthcare system through innovative solutions. They are seeking an AI Engineer II to support AI feature development, participate in AI projects, and assist in model implementation while collaborating with various stakeholders to deliver effective AI solutions.
Responsibilities:
- Support AI feature development: Contribute to AI capabilities for retrieval, ranking, categorization, and generative AI features on unstructured healthcare data, following established patterns and best practices
- Participate in AI projects: Work collaboratively on AI projects from requirements gathering through deployment, supporting stakeholders in delivering models and software that meet business objectives with guidance from senior engineers
- Assist in model implementation: Help build reliable AI systems for production environments, learning proper monitoring and operational practices for deployed models while ensuring quality standards
- Apply established methodologies: Use appropriate evaluation datasets, metrics, and model architectures following team guidelines to build effective AI solutions that connect to business outcomes
- Learn and collaborate: Work closely with product managers, senior engineers, and other team members to integrate AI capabilities, while actively developing your technical skills and contributing to team knowledge sharing
Requirements:
- Bachelor's - Equivalent experience will be considered in lieu of a degree
- Minimum of 2 years of experience
- Experience working with AI/ML systems in production environments, including exposure to search, ranking, or generative AI applications
- Familiarity with prototyping new AI solutions and contributing to projects that moved from concept to implementation
- Understanding of AI development lifecycle components, from model selection through basic productionization with senior guidance
- Growing experience in connecting technical modeling work with business value through collaboration with stakeholders
- Hands-on experience with tools like PyTorch, TensorFlow, and working with pre-trained models from platforms like Hugging Face, plus exposure to deployment tools such as Databricks, AWS Bedrock, or Azure ML