Senior Machine Learning Engineer

Overview In this role you will design, build, and operationalize advanced ML solutions to transform the insurance experience. You’ll work within a global AI team to deliver scalable models and end-to-end pipelines, partnering with data scientists, engineers, and business stakeholders. You’ll drive MLOps practices, ensure reliable production systems, and mentor peers to strengthen engineering culture. This is a high-impact, cross-functional role at the intersection of business goals and cutting-edge AI technology. Compensation / Benefitscompetitive compensationcomprehensive benefitscareer growth and leadership opportunitiesflexible work environmentinclusive culturework-life balance ResponsibilitiesDesign, build, and productionize ML models (including classical ML, DL, and LLM-based solutions)Develop and maintain end-to-end ML pipelines with CI/CD, monitoring, and performance trackingLead technical design reviews and set architecture standards for scalability, reliability, and securityPartner with data scientists, engineers, and stakeholders to deliver AI aligned with business goalsApply and promote MLOps across the full model lifecycleMentor junior engineers and contribute to a strong engineering culture Key requirementsMaster’s or PhD in Computer Science, Engineering, or related quantitative field5+ years of production ML experienceStrong Python programming skills (Java/SQL a plus)Hands-on NLP and document understanding (classification, entity extraction, relationship extraction)Experience with unstructured data (PDFs, images) using vision/language models and OCRUnderstanding of AI lifecycle: data prep, feature engineering, model development, deployment, monitoringExperience with distributed computing (Spark, Hadoop) and cloud platforms (AWS, GCP, or Azure)Familiarity with Docker, Kubernetes, CI/CD, and production-grade engineering practicesstrong collaborationcuriosityownership and accountabilityPythonNLP and document understandingOC R / vision-language models