Member of Technical Staff
OpenEvidence8 months ago
Responsibilities
- Build new medical AI products and capabilities from zero to one and scale them to broad adoption.
- Own and deliver important projects end to end, including implementation, evaluation, launch, and demonstrating impact.
- Develop and evaluate modern machine learning and applied AI systems.
- Build full-stack products, frontend or mobile experiences, robust infrastructure, and site-reliable backends as appropriate to the candidate's strengths.
- Optimize system and product speed to improve user experience and eliminate inefficiencies.
- Make product decisions directly as an engineer or scientist without separate product managers.
Requirements
- Experience pushing the boundaries of modern machine learning models, building applied AI systems, or delivering end-to-end software products.
- Ability to take ownership of major projects and work autonomously in a fast-moving environment.
- Strong interest or experience in one or more areas including machine learning, applied AI, full-stack, frontend, mobile, infrastructure, site reliability, or performance optimization.
- Machine learning candidates should have a research background and an interest in building practical products rather than only writing papers.
- Frontend and mobile candidates should demonstrate exceptional attention to detail and experience creating polished user interfaces.
- Infrastructure and reliability candidates should be motivated to build robust, optimized backends for mission-critical services.
- Ideal candidates are described as brilliant, ambitious, scrappy, precise, motivated, hardworking, and low-ego.
Benefits
- In-person work five days per week in San Francisco or Miami
- Meals and transportation provided
- Additional support to help employees move quickly
Categories
About OpenEvidence
OpenEvidence builds an AI-powered medical information and clinical decision-support platform for clinicians and healthcare organizations, combining search across guidelines, clinical trials, and journals. The product is delivered as cloud-based software and used to retrieve evidence and literature at the point of care. Founded in 2021 and headquartered in Miami, it emerged from the Mayo Clinic Platform Accelerate program and partners with NEJM and JAMA, with backing from Sequoia and Google.