Research Engineer, RL Systems

Research Engineer, RL Systems

SF · NYC

About RoVR


RoVR builds the autonomous system of execution for healthcare: AI that runs clinics end to end, acts across every system they depend on, and improves with every outcome. Healthcare is one of the most complex real-world environments for autonomous intelligence, demanding continuous coordination, reasoning, and decision-making under uncertainty. We’re pushing the frontiers of agentic systems, long-horizon reasoning, memory, and reinforcement learning to build AI that pursues goals, recovers from failures, and learns from experience. We’re building the foundation for a future where entire healthcare systems operate, adapt, and improve autonomously.

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 product builder to own how patients experience RoVR. From finding a provider and booking a first visit to understanding next steps and staying connected between appointments, you would make complex care feel understandable and manageable.

You would also shape how patients interact with agents: when an agent should take initiative, what it should explain, when it should ask for confirmation, and how a person takes over. These decisions are central to the product.

The work combines product judgment, interaction design, and experimentation. You will spend time with patients and care teams, turn observations into prototypes, and work with engineers to ship and evaluate them. You will be accountable for whether people can understand the experience, complete what they came to do, and get the help they need.

Responsibilities

  • Own patient journeys across onboarding, provider discovery, scheduling, intake, communication, and ongoing care.

  • Study how patients and care teams use the product. Turn confusion, abandoned tasks, and repeated requests for help into concrete improvements.

  • Design interactions across the patient portal, chat, and voice. Define how agents communicate progress, handle uncertainty, request consent, and hand work to people.

  • Turn ideas into flows, prototypes, and clear product behavior. Work closely with engineering, design, and clinical operations to carry them through launch.

  • Run experiments with explicit hypotheses and success criteria. Measure task completion, patient understanding, effort, and follow-through.

  • Build experience evaluations with realistic patient scenarios, including interruptions, misunderstood requests, changing preferences, and failed actions. Use them to assess changes before and after release.

  • Make accessibility, health literacy, language needs, and patient control part of the product from the beginning.

Minimum qualifications

  • You have shipped a consumer product or service and can explain the decisions you made, what happened after launch, and what you changed.

  • Strong product judgment and interaction design instincts. You can make a complex process easier without hiding information people need.

  • Ability to turn an idea into a testable prototype using design tools, AI tools, or lightweight code. A software engineering background is not required.

  • Experience speaking directly with users and combining those observations with behavioral data to decide what to build.

  • Clear writing. You can define product behavior precisely and write language that helps someone understand what happens next.

  • A practical understanding of AI capabilities and limitations, including how unpredictable behavior affects the experience.

  • Ownership from problem discovery through launch and iteration.

Preferred qualifications

  • Experience building consumer healthcare products or services that involve sensitive information and consequential decisions.

  • Experience designing conversational, voice, or agent-based experiences.

  • Experience improving onboarding, activation, or ongoing engagement through measurable product changes.

  • Familiarity with accessibility, multilingual experiences, or designing for people with different levels of health and digital literacy.

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.

The Role

We are looking for a research engineer to build the reinforcement learning stack: the systems that run policies against environments, collect and score rollouts, and feed them to the trainer, at the throughput and stability RL on long-horizon agents demands. As the owner of this stack, you would make it possible to run RL experiments in hours instead of weeks, and make the results trustworthy. The work is systems engineering in service of research.

Responsibilities

  • Build and scale the rollout system: distributed episode execution against environments, with sandboxing, scheduling and fault tolerance.

  • Build the asynchronous training loop: rollout and trainer coordination, policy weight distribution, and handling of policy staleness.

  • Serve reward models and verifiers at rollout throughput.

  • Instrument training for stability: importance sampling corrections, training-inference mismatch, and the diagnostics that catch divergence early.

  • Make experiments reproducible and cheap to launch, so researchers run more of them.

Minimum qualifications

  • Bachelor's or master's degree, or equivalent experience, in computer science or a related field.

  • Experience building distributed ML systems, with deep familiarity with PyTorch and at least one RL or post-training framework.

  • Understanding of RL algorithms for language models well enough to implement and debug them.

  • Strong Python and systems skills; experience with GPU scheduling, Ray or similar.

Preferred qualifications

  • Experience with asynchronous or off-policy RL training at scale.

  • Experience with inference engines (vLLM, SGLang) in the training loop.

  • Contributions to open-source RL or training infrastructure.

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.

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