Software Engineer - MLOps

📋 Description

• • Join Phare Health, now part of R1 and its AI innovation engine, R37 Lab, as a Software Engineer specializing in MLOps. You will be instrumental in building the future of healthcare AI, contributing to an AI-native Healthcare Revenue Operating System that leverages advanced clinical reasoning technology to automate medical coding, billing, and follow-up processes. This is a unique opportunity to work on AI systems that are already impacting millions of patient encounters annually across top U.S. health systems, processing hundreds of millions of claims and driving billions of workflow actions. You will experience startup-level ownership with enterprise-level impact, building AI that ships, scales, and demonstrably improves healthcare operations.
• • As a Software Engineer - MLOps, your primary responsibility will be to own and manage the production runtime for Phare's Machine Learning (ML) stack. This involves the end-to-end lifecycle of ML models, from deployment and serving to scaling across various inference endpoints and batch streaming workflows. You will be at the forefront of ensuring our ML systems are robust, reliable, and performant.
• • You will architect and implement progressive delivery pipelines, incorporating automated rollouts and rollbacks to ensure seamless updates and minimize downtime. A key aspect of your role will be managing Service Level Objectives (SLOs) for critical performance metrics such as latency and availability, ensuring our ML services meet stringent operational standards.
• • A significant focus will be placed on instrumenting comprehensive, end-to-end observability. This includes setting up and maintaining metrics, logs, traces, and crucially, monitoring for model drift and regression. This deep visibility will enable proactive identification and resolution of issues, ensuring the continued accuracy and effectiveness of our deployed models.
• • You will leverage industry-leading Infrastructure as Code (IaC) tools like Terraform to manage and provision our cloud infrastructure, ensuring consistency and reproducibility. Containerization with Docker and orchestration with Kubernetes will be central to deploying and managing our ML services and batch processing jobs.
• • Building and maintaining robust CI/CD pipelines is essential for enabling rapid, reliable, and auditable ML releases. You will ensure environment parity across development, staging, and production, and implement best practices for versioning both model artifacts and the data used for training and inference.
• • You will be responsible for hardening the platform, ensuring security, scalability, and maintainability. This includes implementing best practices for access control (RBAC), secrets management, data encryption, and maintaining detailed audit logs for all ML operations.
• • Managing the post-training lifecycle of ML models is a critical component of this role. You will oversee model registries, define and manage stage gates for model promotion, and design and implement strategies for scheduled or event-driven retraining to combat model decay and maintain performance over time.
• • This role offers the opportunity to work on cutting-edge AI technology in a regulated environment, providing valuable experience in healthcare AI. You will collaborate with brilliant, mission-driven teammates who are passionate about making a tangible difference in how healthcare operates.
• • We are hiring across several seniority levels, from Mid-level (L2) to Staff (L4). Depending on your experience, you will either independently deliver end-to-end projects, lead larger projects with increased technical complexity, or lead teams and major cross-functional initiatives. Regardless of level, you will have significant ownership and the opportunity to shape our MLOps strategy and execution.
• • This role requires a hands-on approach to operating ML systems at scale, where the reliability and feedback loops of production systems are as important as the predictive accuracy of the models themselves. You will gain invaluable experience in production ML, deploying and managing models that run on GPUs for both real-time APIs and large-scale batch streaming inference.
• • You will be a key player in ensuring system reliability through progressive delivery strategies, automated testing, and comprehensive monitoring. Your work will directly contribute to the stability and performance of critical healthcare AI applications.
• • This is an opportunity to contribute to a rapidly growing team within a company that is revolutionizing healthcare through AI. You will have the chance to constantly learn, collaborate across diverse groups, and explore new career paths while creating meaningful work that improves patient care and operational efficiency.
• • You will be part of an organization that goes beyond expectations, not only in driving customer success and improving patient care but also in supporting its team members and giving back to the community. This role offers a chance to be part of a culture that values innovation, collaboration, and impact.