Join Tech @ Ro to build the future of healthcare, from the ground up! At Ro, we believe that when people achieve their health goals, they can achieve their life goals. The highest-leverage way to move society forward is to give people their health, and the current healthcare system isn’t built to do that. It was built to bill, not to serve patients. We’re building a new system. One where the patient is in control. One designed from scratch for the digital age. At Ro, technology isn’t just a function… It's core to how we deliver care. We’ve built a vertically integrated healthcare platform that connects telehealth, diagnostics, pharmacy, and logistics into a seamless, end-to-end experience for millions of patients. …and we’re just getting started. As part of Tech @ Ro, you’ll work on systems that operate at scale, with an opportunity to: Solve complex, high-concurrency problems across a full-stack platform Build and ship quickly with tight feedback loops and real-world impact Own systems end-to-end, from architecture to production performance Work alongside experienced operators, technical leaders, and clinicians Help define how modern healthcare should be delivered We’re a performance-driven team with a strong sense of ownership and urgency. We move fast, learn quickly, and hold a high bar for what we build, and do so with a big heart — because patients depend on it. If you’re motivated by impact, scale, and the chance to help lead the patient revolution, come build with us. The Role Ro is building a team focused on shipping LLM-powered products across the patient experience, clinical operations, and internal tooling. We're hiring a Senior Applied AI Scientist to own the evaluation, measurement, and optimization of our AI systems. This role sits at the intersection of data science, applied machine learning, and product engineering. You'll design the frameworks that tell us whether our AI systems are actually working and use those insights to continuously improve them. This is not a research role. You'll work closely with engineers and product teams to evaluate production systems, run experiments, identify failure modes, and ensure our AI products become more accurate, reliable, and cost-effective over time.