AI/ML Engineering Co-op, Zus Health

• Hands-on experience with LLMs and classical ML methods (must-have)
• Hands-on experience with agentic frameworks and tools such as LangGraph, Strands, LangFuse, MCP, etc
• Proficiency in Python (must-have)
• Hands-on experience designing offline or online experiments: crafting task-specific metrics, computing bootstrapped confidence intervals, and conducting slice-based error analysis
• Familiarity with cloud services (e.g., AWS, GCP, Azure)
• Demonstrated curiosity—comfortable jumping into unfamiliar domains, papers, or codebases and learning fast
• Strong verbal/written skills—able to explain complex ML concepts to diverse stakeholders
• Demonstrated ability to work effectively in a collaborative team environment

Desirable

• We are looking for an eager software engineering co-op to help build the next generation of healthtech tools
• This co-op will be part of the AI group. This group has members embedded in the product teams and also works independently on proof-of-concept projects
• The ideal candidate will be able to contribute in either situation
• In your role as an AI/ML Engineer Co-op, you will, under the guidance of senior AI group members, be responsible for conducting research to explore new methodologies and techniques, and integrating them into our product offerings
• You will develop prototypes to test and improve upon your innovations and develop feedback mechanisms to improve models with human oversight
• You will work with software engineers to help deliver CI/CD pipelines, and automate workflows to ensure reliable and scalable model operations. You will be responsible for presenting your learnings and helping the team leverage these methods and techniques
• Algorithm & Experimentation: Formulate hypotheses, build rapid prototypes, and run experiments
• Evaluation & Diagnostics: Design task-specific metrics and effective methods for their estimation
• Collaboration: Work cross-functionally with engineers, product managers, and other AI group members
• End-to-End Ownership: Take prototypes to production, collaborating with engineers to deploy, and continually monitor and evaluate models
• This role will start in January and run through June