Senior ML Platform Architect & Lead Engineer

Allstate; United States; Remote; USD 110,000 - 181,000; Full time

Job summary

Allstate's Data & Analytics Technology organization seeks a Machine Learning Platform Lead to architect, build, and scale enterprise ML platforms. You will guide ML infrastructure, MLOps automation, and model deployment across Azure/AWS/GCP, collaborating with data science, engineering, security, and product teams.

This role blends Hands-on engineering with technical leadership, shaping platform strategy, governance, and cost optimization while delivering reliable, scalable ML capabilities for

Qualifications

• Extensive experience in ML engineering, platform engineering, or large-scale distributed systems.
• Deep hands-on expertise with MLOps tools, ML frameworks, model deployment techniques, and ML lifecycle automation.
• Strong proficiency in Python and backend development for machine learning systems.
• Experience with cloud platforms and ML services, including Azure ML Studio, AWS SageMaker, and/or Google Vertex AI.
• Exposure to cloud storage/data such as Azure Fabric/OneLake, AWS S3, and Google Cloud Storage (GCS).
• Experience with cloud-native scanning and security tools such as Azure Defender, Microsoft Purview, AWS Security Hub, Amazon Inspector, GCP Security Command Center, or equivalent services.
• Strong understanding of technologies such as Kubernetes, Docker, CI/CD, Terraform/Infrastructure-as-Code, etc.
• Solid knowledge of system design, APIs, data pipelines, and scalable ML infrastructure patterns.
• Proven ability to lead technical initiatives and influence cross-team engineering decisions.

Responsibilities

• Serve as the technical lead for ML platform architecture, guiding system design, scalability, performance, and reliability across platform components.
• Architect and build core ML platform services, including training and compute infrastructure, feature stores, model registries, inference runtimes, and data pipelines.
• Drive architectural decisions for distributed systems, cloud-native frameworks, and automated MLOps workflows that support enterprise-scale machine learning.
• Evaluate and integrate emerging ML platform technologies, tools, and best practices to continuously strengthen platform capabilities.
• Design and implement robust MLOps pipelines for experiment tracking, data and model versioning, CI/CD for ML, automated retraining, and model governance.
• Develop automated workflows that ensure reproducible model training, validation, deployment, and lifecycle management across multiple environments.
• Implement monitoring and observability systems for model performance, data quality, drift detection, and inference reliability.
• Build and optimize cloud-based ML infrastructure on Azure, AWS, or GCP using Kubernetes, containerization, and infrastructure-as-code.
• Develop scalable batch and streaming data pipelines using modern data engineering tools and frameworks.
• Embed security, compliance, responsible AI principles, and cost optimization best practices within ML platform architecture and operations.
• Collaborate with data scientists to translate modeling needs into scalable, reusable, and self-service platform capabilities.
• Work closely with security, compliance, and governance teams to ensure safe and compliant deployment of AI/ML solutions.
• Partner with application engineering teams to accelerate adoption of ML services and enable consistent, high-quality production deployments.
• Provide technical mentorship, set engineering standards, and contribute to documentation, best practices, and ongoing platform improvements.

Skills

ML engineering

Platform engineering

Large-scale distributed systems

MLOps tools

Python

Cloud platforms

Azure ML Studio

AWS SageMaker

Google Vertex AI

Kubernetes

Docker

CI/CD

Terraform / IaC

APIs

Tools

Azure ML Studio

AWS SageMaker

Google Vertex AI

Azure Fabric/OneLake

AWS S3

Google Cloud Storage (GCS)

Azure Defender

Microsoft Purview

AWS Security Hub

Amazon Inspector

GCP Security Command Center

Job description

Allstate's Data & Analytics Technology organization seeks a Machine Learning Platform Lead to architect, build, and scale enterprise ML platforms. You will guide ML infrastructure, MLOps automation, and model deployment across Azure/AWS/GCP, collaborating with data science, engineering, security, and product teams.

This role blends Hands-on engineering with technical leadership, shaping platform strategy, governance, and cost optimization while delivering reliable, scalable ML capabilities for