Spring Health aims to revolutionize mental healthcare by removing barriers to access. The Generative AI Platform team is looking for a Machine Learning Engineer to build foundational LLM infrastructure, tools, and automated systems to accelerate the delivery of next-generation AI features for product teams, making them faster, safer, and more reliable.
Requirements
- Demonstrated experience building and delivering production-grade software, with significant, hands-on experience in LLM or Generative AI engineering.
- Strong proficiency in Python and familiarity with the modern AI/ML stack, including cloud services (AWS, GCP, or Azure) and CI/CD pipelines.
- Hands-on experience building or working with key components of the modern LLM stack.
- Direct experience with orchestration frameworks (e.g., LangChain, LangGraph), observability tools (e.g., LangSmith), and the infrastructure for Retrieval-Augmented Generation (RAG) like vector databases is a significant plus.
- The ability to operate at a feature scope, breaking down clearly defined solutions into smaller, manageable tasks.
- A deep understanding of the importance of handling sensitive data.
Responsibilities
- Design, build, and maintain the core components of our LLM infrastructure.
- Operationalize tools like LangSmith for observability.
- Create shared patterns for using orchestration frameworks.
- Develop reusable libraries that make our feature teams more productive.
- Build the platform to support sophisticated LLM use cases.
- Help deploy and build the pipelines for a vector database to enable Retrieval-Augmented Generation (RAG) across multiple product teams.
- Contribute to proofs-of-concept and the architectural groundwork for future innovations, such as exploring the use of an engineered feature store for long-term LLM memory and personalization.
Other
- Candidates must be based in the Salt Lake City metro area and be willing to commute 2-3 days a week when this role transitions to a hybrid schedule in 2026.
- A platform builder's mindset: You think in terms of abstractions, reusability, and creating leverage for other engineers.
- Pragmatic problem-solving.
- Resilience and drive: A high degree of grit and comfort with the ambiguity that comes with a fast-paced, high-growth environment.
- A Bachelor's degree in a technical field or equivalent practical experience.
