Lead Consultant – Machine Learning Platform

Allstate

. Serve as the technical lead for ML platform architecture, guiding system design, scalability, performance, and reliability .

Posted 11/11/2026full-timeRemote • Illinois • United StatesSenior💰 $110,000 - $181,025 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in ML platform architecture, MLOps pipelines, and cloud-native technologies, with a strong focus on system design, scalability, and performance. Proven ability to lead technical initiatives and collaborate effectively with cross-functional teams to enhance ML service adoption and compliance.

Highest-signal resume keywords

ML Platform ArchitectureMLOps Tools ExpertisePython ProficiencyKubernetes and DockerCloud Infrastructure Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ML EngineeringPlatform EngineeringModel Deployment TechniquesData PipelinesCI/CD for MLAutomated WorkflowsModel GovernanceExperiment TrackingData and Model VersioningScalable ML Infrastructure

Soft Skills

Technical MentorshipCross-Team CollaborationInfluencing Engineering Decisions

Tools & Technologies

Azure ML StudioAWS SageMakerGoogle Vertex AIAzure DefenderMicrosoft PurviewAWS Security HubTerraformInfrastructure-as-CodeKubernetesDocker

Industry Keywords

Cloud-Native FrameworksDistributed SystemsModel Performance MonitoringData QualityResponsible AIComplianceCost Optimization

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsDockerGoogle Cloud PlatformKubernetesPythonTerraform

About the role

Key responsibilities & impact

Serve as the technical lead for ML platform architecture, guiding system design, scalability, performance, and reliability
Architect and build 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
Evaluate and integrate emerging ML platform technologies, tools, and best practices
Design and implement MLOps pipelines for experiment tracking, data and model versioning, CI/CD for ML, automated retraining, and model governance
Develop automated workflows for reproducible model training, validation, deployment, and lifecycle management
Implement monitoring and observability for model performance, data quality, drift detection, and inference reliability
Build and optimize cloud-based ML infrastructure using Kubernetes, containerization, and infrastructure-as-code
Develop scalable batch and streaming data pipelines
Embed security, compliance, responsible AI, and cost optimization practices in platform architecture and operations
Collaborate with data scientists to create scalable, reusable, and self-service platform capabilities
Work with security, compliance, and governance teams on safe and compliant AI/ML deployment
Partner with application engineering teams to accelerate ML service adoption and production deployments
Provide technical mentorship, set engineering standards, and contribute to documentation and platform improvements

Requirements

What you’ll need

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 Azure ML Studio, AWS SageMaker, and/or Google Vertex AI
Exposure to 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 Kubernetes, Docker, CI/CD, Terraform/Infrastructure-as-Code, and related technologies
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
6+ years of progressive related experience
Required to submit to a background investigation
Must have a dedicated, private workspace free from distractions, appropriate desk and seating, and reliable internet with minimum speeds of 50 MB download and 5 MB upload
Allstate generally does not sponsor individuals for employment-based visas for this position

Benefits

Comp & perks

Comprehensive technology setup, including a laptop, monitors, headset, keyboard, and mouse
Monthly connectivity reimbursement for eligible employees working from home