Company Name: PURE Insurance

Job Details: Be an Early Applicant Hiring Remotely in United States Remote 145K-175K Annually Mid level

Job Url: https://builtin.com/job/lead-mlops-engineer/6694853

Job 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 workflowso ML lifecycle tools such as MLflow, Data Bundles, Unity Catalogo Code development environments including VSCodeo 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 experienceWant to Learn More?[Our Values][Our Benefits]  [Our Community Impact][Our Leadership]