Machine Learning Engineer

Machine Learning Engineer📍 Hybrid – San Francisco Bay Area, CA💰 $170,000 – $220,000 + EquityAbout the RoleWe're looking for a Machine Learning Engineer to design, build, and deploy ML solutions that support healthcare operations and improve patient experiences. You'll work on predictive models, NLP applications, LLM-powered features, and the scalable AI infrastructure that supports them — partnering closely with Product, Engineering, Data Science, and business stakeholders to bring AI-driven products to market.This is a chance to join a rapidly growing HealthTech company using AI and machine learning to modernize healthcare delivery at scale, and to build solutions that help healthcare organizations make smarter decisions and deliver better outcomes for patients.What You'll DoDesign, build, and deploy machine learning solutions across predictive modeling, NLP, and generative AI/LLM-powered featuresWork with large-scale healthcare datasets, including clinical information, patient engagement data, and operational workflowsDevelop and maintain MLOps pipelines for model training, deployment, monitoring, and evaluationCollaborate cross-functionally with Product, Engineering, Data Science, and business teams to ship AI-driven productsTech StackPython, PyTorch, AWS, Databricks, SQL, Docker, and modern machine learning frameworksWhat We're Looking For3–7+ years of experience building production machine learning systems, with strong software engineering fundamentalsExperience with MLOps practices (training, deployment, monitoring, evaluation)Preferred: background in Healthcare, HealthTech, or Life Sciences, and/or experience with NLP, recommendation systems, predictive analytics, or Generative AIComfort working in a fast-paced, collaborative environment and solving complex, ambiguous problemsCompensation & BenefitsCompetitive base salary ($170,000–$220,000), equity, comprehensive benefits, and flexible working arrangements.