PURE Insurance

Compensation

Full Description

About the Role: We are investing heavily in growing our Data Science and Machine Learning capabilities across underwriting, claims, and customer experience. The Lead MLOps Engineer is a net new role designed to help scale our AI/ML operations function. You’ll play a pivotal part in designing and building the foundation for MLOps within the organization while partnering with stakeholders across the business. Key Responsibilities: • Build and maintain end-to-end MLOps pipelines encompassing model development, deployment, monitoring, and lifecycle management. • Define and implement CI/CD workflows for ML models, ensuring versioning, reproducibility, and scalability. • Establish frameworks and reusable tools that empower data scientists and developers to deploy and monitor models efficiently. • Develop and enforce governance frameworks supporting model explainability, ethical AI practices, and compliance. • Collaborate with cross-functional stakeholders to align technical solutions with business needs. • Contribute to the design of LLMOps capabilities as part of our forward-looking AI strategy. • Provide technical mentorship and help shape future MLOps team growth. Minimum Qualifications: • 2+ years of hands-on MLOps experience, with additional experience as a data scientist or software engineer considered. • Expertise with: o Python (including libraries such as Pandas, Polars, PySpark, TensorFlow, PyTorch) o SQL and DataFrame-based processing workflows o ML lifecycle tools such as MLflow, Data Bundles, Unity Catalog o Code development environments including VSCode o CI/CD pipelines using tools such as GitHub Actions or similar • Familiarity with monitoring frameworks and observability concepts for ML systems. • Strong understanding of governance principles including model versioning, reproducibility, explainable AI, and ethical AI practices. • Demonstrated ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders. • Proven ability to collaborate across teams in a structured, transparent manner. Preferred Qualifications: • Experience supporting property and casualty insurance business use cases. • Familiarity with Databricks. • Exposure to LLMOps concepts and tooling. The base salary for this role can range from $145,000 to $175,000 based on a full-time work schedule. An individual’s ultimate compensation will vary depending on job-related skills and experience, geographic location, alignment with market data, and equity among other team members with comparable experience Want to Learn More? [Our Values] [Our Benefits] [Our Community Impact] [Our Leadership] PURE Insurance is a property and casualty insurance company—think homes, cars, fine art and collections—designed exclusively for financially successful individuals and families. We're dedicated to delivering an exceptional experience to our members by alleviating stress, solving challenges and removing conflict, wherever possible, from the insurance process. We are deeply committed to fostering a work environment where everyone has an equitable chance to learn, develop and succeed, and where all feel welcome, safe, and supported to do their best work and bring their whole self to PURE. Our team is comprised of empathetic, passionate and curious individuals who are #PUREproud of the work we do and milestones we achieve together. We’re constantly looking for bright individuals with ambitions as high as our own to join our community and contribute to our journey. Joining PURE means creating your own journey, too. We encourage our team members to pursue their personal passions and provide them resources and support to see them come to fruition. Learn more about our culture on LinkedIn. Interested in PURE but don’t see a role that fits? Introduce yourself and we’ll get in touch if an opportunity opens up that seems like a good match.