Clinical Data Intelligence platform that leverages cutting-edge AI, Machine Reading, and Knowledge Graph technology to automate cognitive tasks involving clinical data. Our solutions directly empower clinicians, researchers, and care coordinators to improve efficiency, reduce frustration, and enhance patient care.
Requirements
- 7+ years of full-time (not internship or contract) experience in AI/ML or full stack software engineering, specifically with data-intensive systems.
- Strong background in software engineering, AI/ML/NLP engineering, and data analytics/engineering.
- Proficiency in Python and SQL along with experience using core data tools like PostgreSQL, dbt, and BigQuery.
- Hands-on experience with ML/AI technologies such as LLM prompt engineering and frameworks like PyTorch.
- Experience with cloud platforms (e.g., Google Cloud Platform), Linux, bash scripting, and building web services (e.g., Django, FastAPI).
- Comfortable developing secure systems and processes in compliance with regulated standards.
- Experience with front-end technologies like TypeScript and React.
Responsibilities
- Build and improve clinical/health information extractors and summarizers that utilize advanced Machine Learning (ML), Natural Language Processing (NLP), and Large Language Model (LLM) prompt engineering.
- Design, implement, and maintain robust data pipelines to scrape, collect, extract, transform, query, analyze, mine, and distill both structured and unstructured data.
- Contribute to expanding and refining our clinical knowledge graph and building supporting data/AI/ML systems and automations to evaluate system quality and performance.
- Develop and deploy secure code, upholding the confidentiality, integrity, and availability of information systems in compliance with HIPAA and SOC 2.
- Participate in rotating on-call duties to ensure continuous system uptime and reliability.
Other
- Must be authorized to work in the United States.
- Must be able to work during core hours in the Pacific timezone.
- H1B transfers are available (we cannot sponsor new H1B visas).
- Hybrid schedule (San Francisco office once or more weekly).
- Work on cutting-edge technology (Machine Reading, Knowledge Graphs, LLMs) to solve real-world problems that directly influence patient care and medical efficiency.
