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 an engineer to build and run the data foundry: the pipeline that turns the continuous record of work clinics produce into training data through ingestion, de-identification, curation and synthetic generation. As the owner of that pipeline, you would decide what the models learn from and be able to defend every example in the set.
Responsibilities
Build ingestion from production: agent trajectories, human edits and clinical records into versioned, queryable datasets.
Own de-identification and provenance so every training example traces to its source and its consent basis.
Curate: filtering, deduplication, labeling design, quality scoring and mixture selection for SFT, preference and RL data.
Build synthetic data generation on top of our simulation environments, and measure where it helps and where it hurts.
Give Post-Training and Evals exactly the data they need, and the metrics that say whether it is improving.
Minimum qualifications
Bachelor's or master's degree, or equivalent experience, in computer science, machine learning or a related field.
3+ years building data pipelines for ML training, with experience deciding what goes into a training set and why.
Strong Python and a large-scale processing framework (Spark, Ray, Beam or similar).
ML fundamentals; you know how data choices show up in model behavior.
Experience with synthetic data, LLM-based labeling or filtering.
Rigor about privacy. De-identification is an engineering problem with tests, not a checkbox.
Preferred qualifications
Healthcare data formats (FHIR, HL7, EHR exports) and their failure modes.
Building data products for external partners.
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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