NY, SF, Remote
Why RoVR
At RoVR, we’re on a mission to turn practices into AI-Native, Self-Optimizing Learning Health Clinics. At RoVR, we are building a multimodal, agentic operating system to launch, manage, and scale A-LHCs nationwide. We collaborate with large health organizations as well as local physician groups, modernizing legacy operations to launch these next-generation clinics.
Central to this vision are at RoVR, autonomous agents that orchestrate and optimize clinical, administrative, and patient engagement processes. By alleviating repetitive tasks, RoVRs free providers and admins to focus on proactive decision-making guided by actionable insights, laying the groundwork for a more responsive, outcome-driven healthcare ecosystem.
By uniting clinical and operational intelligence in one cohesive platform, we're building the infrastructure for a Learning Health System that can collaborate with and empower clinicians to redefine the patient experience and transform health outcomes.
Based in the heart of NYC and backed by leading venture capital firms/visionary healthcare leaders, RoVR is on a mission to transform the future of healthcare. We are seeking mission-driven engineers, designers, and operators to join our team and help us build the foundational operating system that will drive medicine for the next century.
The Role
We are looking for a research scientist to study how a model learns from what happens after it acts. As the owner of the learning method, you would decide how to turn sparse, delayed and partly subjective feedback from clinical work into learning signal, how to assign credit across long tool-using tasks, and how much reasoning a given action needs. The work combines fundamental research with implementation in our training runs.
Responsibilities
Set the post-training research agenda: which methods, against which signal, and the experiments that settle it.
Design reward models, verifiers and preference signals from human feedback, and study where they fail.
Develop RL for long-horizon, tool-using agents: policy optimization, advantage estimation, exploration, curriculum.
Study reasoning: when it helps, when it costs more than it returns, and how to train for the right amount.
Work in the stack directly. Ideas are implemented, run and measured by the person who had them.
Minimum qualifications
Master's degree or equivalent research experience in machine learning, computer science or a related field.
Hands-on RL training of language models with results you can show.
Research that produced measurable model improvements, published or not.
Small-scale experiments whose conclusions survive scale.
Comfort implementing and debugging in a complex training codebase.
Rigor, and a preference for being proven wrong quickly.
Preferred qualifications
PhD or equivalent depth in RL, reasoning or post-training.
Agentic, multi-turn or execution-feedback RL.
Logistics
Location: San Francisco or New York, on-site.
Employment type: full-time.
Compensation: competitive salary and meaningful equity.
Visa sponsorship is available.
RoVR is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
Apply for this Job