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Senior MLOps Machine Learning Engineer - Insurance

AllstateChicago, Illinois🇺🇸United StatesPosted Oct 16, 2026

Why This Role Stands Out

This hybrid role at a reputable company like Allstate offers immense growth potential as you'll design, build, and deploy impactful AI/ML solutions while mentoring junior engineers and driving MLOps best practices. You'll thrive here if you're a skilled engineer passionate about translating complex data into measurable business impact and eager to collaborate within a dynamic team environment. Apply today to shape the future of insurance technology and further develop your expertise in a leading organization.

Quick Overview

Seniority
Mid Senior
Employment type
Full Time
Work mode
Hybrid
Location
Chicago, Illinois, United States
GCPMicroservicesSQLAWSMLOpsMachine LearningAzureDeep LearningGitPython

Job Description

Allstate is seeking a Senior AI Engineer to join our Data Science & Artificial Intelligence (AI) team in the Insurance industry. You will design, build, and deploy scalable AI/ML solutions that improve underwriting, claims, fraud detection, and customer experiences. Responsibilities include developing production-grade models, collaborating with data scientists and engineers, integrating models into cloud-based systems, and ensuring reliability, fairness, and compliance. You will mentor junior teammates, drive MLOps best practices, and partner with business stakeholders to translate complex data into measurable business impact.

Responsibilities

  • Design, build, and deploy scalable AI/ML solutions for underwriting, claims, and fraud detection
  • Collaborate with data scientists and engineers to productionize and optimize models
  • Implement MLOps pipelines, CI/CD, monitoring, and model governance
  • Integrate AI services and APIs into cloud-native applications and data platforms
  • Ensure AI systems meet security, reliability, fairness, and regulatory requirements
  • Work with stakeholders to translate business needs into technical AI solutions
  • Optimize model performance, latency, and cost in cloud environments
  • Mentor junior engineers and contribute to engineering best practices and standards
  • Document architectures, models, and processes for maintainability and reuse
  • Evaluate and introduce new AI tools, frameworks, and practices to drive innovation

Required Skills

  • Python
  • Machine learning algorithms
  • Deep learning frameworks (Tensor
  • Flow/Py
  • Torch)
  • MLOps and ML pipelines (CI/CD)
  • Cloud platforms (AWS/Azure/GCP)
  • Data engineering (SQL, data pipelines)
  • Model monitoring and observability
  • API development and microservices
  • Version control (Git)
  • Software engineering best practices

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