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Principal Machine Learning Engineer
GoodRx · Flexible / Remote
Publicada em 24/04/2026
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GoodRx is the leading prescription savings platform in the U.S. Trusted by more than 25 million consumers and 750,000 healthcare professionals annually, GoodRx provides access to savings and affordability options for generic and brand-name medications at more than 70,000 pharmacies nationwide, as well as comprehensive healthcare research and information. Since 2011, GoodRx has helped consumers save nearly $75 billion on the cost of their prescriptions.Our goal is to help Americans find convenient and affordable healthcare. We offer solutions for consumers, employers, health plans, and anyone else who shares our desire to provide affordable prescriptions to all Americans.Major Responsibilities:Define and drive machine learning strategy across multiple domains and product areas while actively contributing to implementationDesign, build, and scale production ML systems, pipelines, and servicesEstablish standards for model architecture, evaluation, deployment, and lifecycle managementLead development of complex ML solutions, partnering with Data Scientists to bring models into productionLeverage agentic AI to speed up development and deliver features on a consistent cadenceDrive enterprise MLOps strategy, including deployment, monitoring, and model governanceDefine and implement scalable feature engineering and data pipeline strategiesLead cross-functional initiatives to improve ML system performance, reliability, and scalabilitySolve highly complex, ambiguous technical problems through hands-on development and technical leadershipMentor senior engineers and influence technical direction across teamsEvaluate and adopt new tools, technologies, and best practices to advance ML capabilitiesSkills & Qualifications:10+ years of experience building and deploying machine learning systems at scaleProven track record of leading and delivering large, complex ML initiativesStrong expertise in ML frameworks (e.g., TensorFlow, PyTorch, XGBoost) and distributed systemsExtensive p
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