Fabric Health is looking to solve healthcare's capacity problem by developing advanced language and voice technologies to improve patient and provider interactions.
Requirements
- 5+ years of experience in software engineering or applied machine learning, with a strong focus on building real-world AI/ML systems.
- Proficiency in backend development using Python (Flask or FastAPI), and 3+ years of hands-on experience with LLMs and LLM agents.
- Solid understanding of embeddings and embedding databases.
- Experience in NLP or speech processing technologies.
- Familiarity with modern AI/ML frameworks and tools (e.g., Hugging Face, OpenAI API, LangChain, LangGraph).
- Experience building and deploying cloud-native applications on AWS with Kubernetes and container tools.
- Demonstrated ability to bring models from research to production, solving for latency, scale, and reliability.
Responsibilities
- Designing, building, and optimizing LLM applications (e.g., RAG, classification, summarization).
- Prototyping and productionizing ML and AI features in Python, integrating them with backend services.
- Collaborating with engineering to develop APIs for LLM applications used by other product components.
- Creating automated evaluations to measure the accuracy and performance of LLM-powered systems.
- Maintaining and improving existing NLP and AI diagnosis production components.
- Deploying AI services end-to-end in cloud-native environments using AWS and Kubernetes.
- Staying on the cutting edge by researching and testing new AI tools, APIs, and architectures.
Other
- You care deeply about the mission: You are passionate about deploying technology that empowers patients to engage with healthcare in their preferred language and format.
- You're an autonomous problem solver: You excel at breaking down complex problems in the AI space and finding effective solutions, operating with autonomy and ownership.
- You're a leader in your field: You stay current on machine learning, foundation models, and algorithms related to text and text-to-speech technologies.
- You value robust and responsible AI: You're committed to building robust testing and monitoring pipelines that provide insight into real-time performance, and you are dedicated to developing safeguards for responsible AI use.
- You thrive on collaboration: You enjoy working cross-functionally across teams, integrating AI use cases into products by understanding their APIs and data systems.
