Senior Data Scientist role focused on building and deploying data-driven agentic AI solutions, including LLM integration, cloud infrastructure, and observability, within an enterprise AI risk and governance context.

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.

The Principal Engineer will be the technical authority for the AI, Security Operations Data, and security tooling ecosystem underpinning Cyber Operations. This role defines and enforces engineering standards for shared AI and data capabilities, ensuring reliability, security, observability, and auditability at enterprise scale. It also supports the integration of security-relevant tooling into the ecosystem with consistent patterns and automated controls.

Distinguished Engineer role at Allstate focusing on leveraging AI and GenAI to transform cybersecurity practices and software delivery. The role involves pioneering complex enterprise problems, integrating AI solutions, and mentoring engineers while staying on the cutting edge of technology.

This role involves architecting, designing, and implementing AI and machine learning applications, particularly generative AI and RAG patterns, for the insurance industry. The developer will build and manage these applications in production, focusing on automating and enhancing insurance processes, and ensuring AI-based KPIs are met. The role also includes building traditional microservices and establishing CI/CD pipelines.

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.

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.

This role focuses on implementing generative and agentic AI technologies to automate and optimize software development workflows, specifically for internally-used digital products supporting enterprise infrastructure and incident management. The position involves full-stack development using Java and JavaScript, with a focus on integrating AI capabilities into the ServiceNow portal and development pipelines.