Insurance · Insurance
Currently tracking 9 active AI roles, up 216% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $75k–$291k (avg $151k).
| Title | Stage | AI score |
|---|---|---|
| Applied Machine Learning Engineer (All Levels) Allstate is seeking Machine Learning Engineers to design, build, and operate ML models across the full ML lifecycle, from data exploration to deployment and monitoring. The role involves working with Python, ML libraries like scikit-learn and XGBoost, and SQL, with opportunities to learn cloud platforms and deep learning techniques. The position emphasizes pair programming and test-driven development, with varying responsibilities based on experience level. | Serve | 7 |
| Machine Learning Platform Engineer Allstate is seeking a Machine Learning Platform Engineer to design, build, and scale the foundational platforms for enterprise-wide ML development and deployment. This role involves working with cloud-native infrastructure, MLOps tooling, and model lifecycle automation to accelerate AI/ML adoption and enable data scientists to build production-ready models. | Serve | 7 |
| Machine Learning Platform - Lead Engineer Lead Engineer for an enterprise ML platform, focusing on architecting, building, and scaling core services like training infrastructure, feature stores, model registries, and inference runtimes. The role involves driving MLOps automation, cloud-native engineering on Azure, AWS, or GCP, and enabling reliable, scalable, and responsible ML adoption across the company. |
| Serve |
| 7 |
| Senior AI Cloud Platform Engineer This role focuses on building and operating cloud application development and hosting platforms for GenAI, enabling developers to build, deploy, and operate AI applications. It involves developing self-service tools, managing infrastructure as a service, and integrating various AI components and APIs. | Serve | 7 |
| Senior Manager - Analytics Data Platform Senior Manager for the Analytics Data Platform team at Arity (Allstate), responsible for leading a team of data and infrastructure engineers. The role involves developing and managing cloud-based big data systems, implementing data processing pipelines and AI solutions, and establishing MLOps best practices. The focus is on enabling data science and analytics teams by providing robust data solutions and infrastructure. | Serve | 5 |