~2mo ago

AI Platform Engineering - MLOps/DevOps

EngineeringOtherPlatform EngineeringDevops Engineer

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Quick Summary

Overview

Design scalable, secure, and reliable infrastructure to support AI/ML workloads Build and implement MLOps pipelines to streamline model development, testing,

Technical Tools

EngineeringOtherPlatform EngineeringDevops Engineer

Design scalable, secure, and reliable infrastructure to support AI/ML workloads
Build and implement MLOps pipelines to streamline model development, testing, and deployment
Manage the end-to-end lifecycle of ML models, from development through retirement
Set up monitoring and observability systems to track model performance, drift, and health in production
Implement governance controls to ensure AI systems are compliant, auditable, and responsibly managed
Integrate AI/ML platforms and models with existing enterprise systems and workflows

Requirements

~1 min read

6+ years of relevant experience in AI platform engineering, MLOps, or DevOps roles
Strong hands-on experience in AI infrastructure architecture and design
Proven expertise in MLOps implementation and CI/CD pipelines for ML
Solid understanding of model lifecycle management practices
Experience with model monitoring and observability tools and frameworks
Familiarity with AI governance controls and compliance requirements
Experience with integration with enterprise systems (APIs, data pipelines, cloud platforms)