Abridge
Software Engineering Intern, Spring
About this role
Abridge seeks Software Engineering Interns for a 3-month Spring 2027 program to build AI-powered clinical features that transform medical conversations into structured documentation. You'll work on end-to-end feature development, LLM workflows, and bug fixes while gaining mentorship in a healthcare AI startup environment.
What you'll do
- Design and build end-to-end features for agentic LLM workflows including retrieval pipelines, tool use, and chained LLM calls
- Fix user-facing bugs and implement quality-of-life improvements across backend and frontend systems
- Develop and work with evaluation frameworks measuring accuracy, robustness, and clinical reliability
- Prototype with new models, prompting techniques, and orchestration tools like LangChain and LlamaIndex
- Collaborate across cross-functional teams (design, product, ML, infrastructure) to ship features to customers
- Build user-centric understanding of clinician workflows and challenges
What they're looking for
- Full-stack software engineering (backend and frontend development)
- LLM orchestration and prompt engineering
- AI/ML frameworks and tools (LangChain, LlamaIndex)
- Debugging and testing methodologies
- Cross-functional collaboration and communication
- Adaptability and rapid learning in startup environments
- Knowledge of AI evaluation and verification practices
- Proficiency with generative AI tools
Benefits
- Mentorship from experienced software engineers
- Hands-on experience with cutting-edge generative AI in healthcare
- Possibility of return offer for full-time role in 2027
- Relocation support and reimbursements to San Francisco
- Flexible work environment and inclusive culture
- Opportunity to make meaningful impact on clinical workflows
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Abridge
Abridge builds an AI platform that transforms healthcare conversations into clinical documentation using advanced natural language processing and generative AI. The company is hiring ML infrastructure engineers, implementation engineers, and machine learning scientists to develop model serving systems, manage customer deployments, and advance medical NLP research.
- Website
- abridge.com
Likely interview questions
- Tell us about a time you debugged a complex system—walk us through your approach and what you learned.
- How do you currently use AI tools in your development workflow, and how do you know when to trust versus verify the output?