Applied AI Engineer (R37)

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At R1, we’re transforming how healthcare works by combining nearly two decades of revenue cycle expertise with advanced technology, including analytics, AI, intelligent automation and workflow orchestration. We pair that technology with the irreplaceable expertise of our people to help hospitals, health systems and medical groups improve financial performance, simplify administrative complexity and create better experiences for patients and providers. All Together Better defines our culture and the way we work. We’re a diverse, global team united by a shared mission to make healthcare work better for all. Across technology, operations and support functions, our people bring deep expertise, empathy and ingenuity to the work we do. Here, collaboration fuels progress, adaptability sparks innovation and every voice can help shape what’s next for R1 and the future of healthcare. About R37 R37 is R1’s AI innovation lab, building technology to transform healthcare. Our flagship platform, Phare OS, uses AI and automation to improve critical pre-bill workflows, including authorization, utilization management, documentation and coding. By identifying and resolving issues before claims are submitted, Phare OS helps prevent denials, improve reimbursement and move revenue cycle work upstream. What makes R37 different is the opportunity to build advanced AI at real-world scale. R1 works across 95 of the top 100 U.S. health systems, giving R37 access to the data, workflows and reach needed to make an immediate impact: 180M+ claims 550M+ patient encounters 1.2B+ workflow actions and outcomes annually This is startup-level ownership with enterprise-level impact. You’ll build technology that moves from idea to real healthcare environments, solving complex problems at scale and changing how healthcare works. As our Applied AI Scientist, you will help transform complex healthcare workflows into reliable, production-ready AI solutions that improve clinical and revenue cycle outcomes. Every day you will design and optimize AI agents for healthcare use cases, evaluate and improve model performance through rigorous testing and feedback loops, and collaborate with clinical, product, and engineering teams to translate real-world challenges into scalable AI systems. To thrive in this role, you must be highly proficient in Python, passionate about building dependable AI systems, comfortable navigating ambiguity, and excited about solving complex healthcare problems using agentic AI, machine learning, and LLM technologies. Here's what you will experience working as an Applied AI Scientist: Design, build, and iterate on agentic AI systems for complex healthcare workflows, including documentation, coding, denial management, appeals, and revenue cycle automation. Develop long-horizon agent behavior across context construction, retrieval, tool use, memory, routing, verification, escalation, and human-in-the-loop review. Define what “good” looks like for clinical agents end-to-end, translating expert workflows into specifications, rubrics, gold standards, test cases, and clinically meaningful success criteria. Build rigorous evaluation and feedback loops using expert review, production logs, model outputs, and benchmarks to measure performance, regressions, edge cases, safety, reliability, provenance quality, and business impact. Prototype new AI capabilities from 0 → 1, then harden them into reliable, explainable, auditable production systems with clear contracts, monitoring, evidence, rationale, and performance gates. Partner with research and ML engineering teams on model selection, fine-tuning, reward modeling, distillation, synthetic data, post-training, and internal AI infrastructure, including instrumentation, experiment tracking, benchmarking, prompt/version management, and reproducible evaluation. Required Skills: 4+ years of experience in software engineering, machine learning engineering, applied AI, research engineering, or a related field. Strong

在R1，我们正在通过将近二十年的收入周期专业知识与先进技术相结合，包括分析、AI、智能自动化和工作流编排，来改变医疗保健的运作方式。我们将这些技术与员工不可替代的专业知识相结合，帮助医院、卫生系统和医疗集团改善财务绩效、简化行政复杂性，并为患者和提供者创造更好的体验。All Together Better定义了我们的文化和工作方式。我们是一个多元化、全球化的团队，共同的使命是让医疗保健为所有人更好地运作。在技术、运营和支持职能部门中，我们的员工以深厚的专业知识、同理心和创造力投入到工作中。在这里，协作推动进步，适应性激发创新，每一个声音都能帮助塑造R1的下一步以及医疗保健的未来。关于R37 R37是R1的AI创新实验室，构建技术以改变医疗保健。我们的旗舰平台Phare OS利用AI和自动化来改善关键的账单前工作流，包括授权、利用管理、文档和编码。通过在索赔提交之前识别和解决问题，Phare OS帮助防止拒赔、改善报销并将收入周期工作向上游推进。R37的不同之处在于有机会在真实世界规模上构建先进的AI。R1与美国排名前100的卫生系统中的95家合作，使R37能够获得所需的数据、工作流和覆盖范围，从而产生即时影响：1.8亿+索赔 5.5亿+患者就诊 每年12亿+工作流操作和结果 这是初创级别的所有权与企业级别的影响力。你将构建从想法走向真实医疗环境的技术，大规模解决复杂问题并改变医疗保健的运作方式。作为我们的应用AI科学家，你将帮助将复杂的医疗保健工作流转化为可靠、生产就绪的AI解决方案，改善临床和收入周期成果。每天你将设计和优化用于医疗保健用例的AI代理，通过严格的测试和反馈循环评估和改进模型性能，并与临床、产品和工程团队合作，将现实世界的挑战转化为可扩展的AI系统。要在这个角色中茁壮成长，你必须精通Python，热衷于构建可靠的AI系统，能够自如应对模糊性，并热衷于使用代理AI、机器学习和LLM技术解决复杂的医疗保健问题。以下是您作为应用AI科学家将体验到的内容：为复杂的医疗保健工作流设计、构建和迭代代理AI系统，包括文档、编码、拒赔管理、申诉和收入周期自动化。开发跨上下文构建、检索、工具使用、记忆、路由、验证、升级和人在回路审查的长周期代理行为。端到端定义临床代理的“好”是什么样的，将专家工作流转化为规范、评分标准、黄金标准、测试用例和具有临床意义的成功标准。使用专家审查、生产日志、模型输出和基准构建严格的评估和反馈循环，以衡量性能、回归、边缘案例、安全性、可靠性、来源质量 and 业务影响。从0 → 1原型化新的AI能力，然后将其加固为可靠、可解释、可审计的生产系统，具有清晰的契约、监控、证据、理由和性能门控。与研究 and ML工程团队合作进行模型选择、微调、奖励建模、蒸馏、合成数据、后训练和内部AI基础设施，包括仪表化、实验跟踪、基准测试、提示/版本管理和可复现评估。所需技能：4+年软件工程、机器学习工程、应用AI、研究工程或相关领域经验。强大的

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